Francisco Herrera Triguero
Contact
herrera@decsai.uaVloC9Ijigr.es
Organization
UGRHighly Cited Researcher 2014, 2015, 2016, 2017, 2018, 2019 and 2020 View CV
| Total | From 2021: | |
|---|---|---|
| Citas | Total: 171094 | From 2021: 87138 |
| Índice H | Total: 190 | From 2021: 132 |
| Índice i10 | Total: 829 | From 2021: 602 |
Papers (993)
| Title | Authors | Year |
|---|---|---|
| A Tutorial on Federated Learning from Theory to Practice: Foundations, Software Frameworks, Exemplary Use Cases, and Selected Trends | MV Luzón, N Rodríguez-Barroso, A Argente-Garrido, D Jiménez-López, .... | 2024 |
| An Interpretable Client Decision Tree Aggregation process for Federated Learning | A Argente-Garrido, C Zuheros, M Luzón, F Herrera. | 2024 |
| Multiobjective Evolutionary Pruning of Deep Neural Networks with Transfer Learning for improving their Performance and Robustness | J Poyatos, D Molina, A Martínez, J Del Ser, F Herrera. | 2023 |
| Explainable Artificial Intelligence (XAI): What we know and what is left to attain Trustworthy Artificial Intelligence | S Ali, T Abuhmed, S El-Sappagh, K Muhammad, JM Alonso-Moral, .... | 2023 |
| Explainable Crowd Decision Making methodology guided by expert natural language opinions based on Sentiment Analysis with Attention-based Deep Learning and Subgroup Discovery | C Zuheros, E Martínez-Cámara, E Herrera-Viedma, IA Katib, F Herrera. | 2023 |
| Multi-step Histogram Based Outlier Scores for Unsupervised Anomaly Detection: ArcelorMittal Engineering Dataset Case of Study | I Aguilera-Martos, M García-Barzana, D García-Gil, J Carrasco, D López, .... | 2023 |
| Connecting the Dots in Trustworthy Artificial Intelligence: From AI Principles, Ethics, and Key Requirements to Responsible AI Systems and Regulation | N Díaz-Rodríguez, J Del Ser, M Coeckelbergh, ML de Prado, .... | 2023 |
| Fuzzy attention neural network to tackle discontinuity in airway segmentation | Y Nan, J Del Ser, Z Tang, P Tang, X Xing, Y Fang, F Herrera, W Pedrycz, .... | 2023 |
| An improved multiplicative acceptability consistency-driven group decision making with triangular fuzzy reciprocal preference relations | M Li, X Liu, Y Xu, F Herrera. | 2023 |
| Generalizing max pooling via (a, b)-grouping functions for Convolutional Neural Networks | I Rodriguez-Martinez, T da Cruz Asmus, GP Dimuro, F Herrera, Z Takáč, .... | 2023 |
| Fusing anomaly detection with false positive mitigation methodology for predictive maintenance under multivariate time series | D López, I Aguilera-Martos, M García-Barzana, F Herrera, D García-Gil, .... | 2023 |
| Design and consensus content validity of the questionnaire for b-learning education: A 2-Tuple Fuzzy Linguistic Delphi based Decision Support Tool | R Montes, C Zuheros, J Morales, N Zermeño, J Duran, F Herrera. | 2023 |
| Revisiting Histogram Based Outlier Scores: Strengths and Weaknesses | I Aguilera-Martos, J Luengo, F Herrera. | 2023 |
| General Purpose Artificial Intelligence Systems (GPAIS): Properties, definition, taxonomy, societal implications and responsible governance | I Triguero, D Molina, J Poyatos, J Del Ser, F Herrera. | 2023 |
| On Generating Trustworthy Counterfactual Explanations | J Del Ser, A Barredo-Arrieta, N Díaz-Rodríguez, F Herrera, A Saranti, .... | 2023 |
| Explainable artificial intelligence (XAI) 2.0: A manifesto of open challenges and interdisciplinary research directions | L Longo, M Brcic, F Cabitza, J Choi, R Confalonieri, J Del Ser, R Guidotti, .... | 2023 |
| Democratic consensus reaching process for multi-person multi-criteria large scale decision making considering participants’ individual attributes and concerns | X Liu, Y Xu, Z Gong, F Herrera. | 2022 |
| Uncertainty quantification in Neural Networks by Approximate Bayesian Computation: Application to fatigue in composite materials | J Fernández, M Chiachío, J Chiachío, R Muñoz, F Herrera. | 2022 |
| FW-SMOTE: a feature-weighted oversampling approach for imbalanced classification | F Madolnado, S., Vareti, C., Fernández, A., Herrera. | 2022 |
| Human pose estimation for mitigating false negatives in weapon detection in video-surveillance | A Lamas, S Tabik, AC Montes, F Pérez-Hernández, J García, R Olmos, .... | 2022 |
| Action Recognition for Anomaly Detection Using Transfer Learning and Deep Architectures | FL Sánchez, S Tabik, F Herrera. | 2022 |
| Personalised Federated Learning with BERT Fine Tuning. Case Study on Twitter Sentiment Analysis | JA Ruiz-Millán, E Martínez-Cámara, M Victoria Luzón, F Herrera. | 2022 |
| Survey on Federated Learning Threats: concepts, taxonomy on attacks and defences, experimental study and challenges | N Rodríguez-Barroso, DJ López, M Luzón, F Herrera, E Martínez-Cámara. | 2022 |
| EvoPruneDeepTL: An Evolutionary Pruning Model for Transfer Learning based Deep Neural Networks | J Poyatos, D Molina, A Martinez, J Del Ser, F Herrera. | 2022 |
| Backdoor attacks-resilient aggregation based on Robust Filtering of Outliers in federated learning for image classification | N Rodríguez-Barroso, E Martínez-Cámara, MV Luzón, F Herrera. | 2022 |
| TimeSpec4LULC: a global multispectral time series database for training LULC mapping models with machine learning | R Khaldi, D Alcaraz-Segura, E Guirado, Y Benhammou, A El Afia, .... | 2022 |
| Handling Imbalanced Classification Problems With Support Vector Machines via Evolutionary Bilevel Optimization | A Rosales-Pérez, S García, F Herrera. | 2022 |
| Course Recommendation based on Sequences: An Evolutionary Search of Emerging Sequential Patterns | MI Al-Twijri, JM Luna, F Herrera, S Ventura. | 2022 |
| A Trust Risk Dynamic Management Mechanism Based on Third-Party Monitoring for the Conflict-Eliminating Process of Social Network Group Decision Making | M Li, Y Xu, X Liu, F Chiclana, F Herrera. | 2022 |
| Exploring the Trade-off between Plausibility, Change Intensity and Adversarial Power in Counterfactual Explanations using Multi-objective Optimization | J Del Ser, A Barredo-Arrieta, N Díaz-Rodríguez, F Herrera, A Holzinger. | 2022 |
| Crowd Decision Making: Sparse Representation Guided by Sentiment Analysis for Leveraging the Wisdom of the Crowd | C Zuheros, E Martínez-Cámara, E Herrera-Viedma, F Herrera. | 2022 |
| Regret Theory-Based Three-Way Decision Method on Incomplete Multi-Scale Decision Information Systems With Interval Fuzzy Numbers | J Deng, J Zhan, E Herrera-Viedma, F Herrera. | 2022 |
| TSFEDL: A Python Library for Time Series Spatio-Temporal Feature Extraction and Prediction using Deep Learning | I Aguilera-Martos, ÁM García-Vico, J Luengo, S Damas, FJ Melero, .... | 2022 |
| Sentinel2GlobalLULC: A Sentinel-2 RGB image tile dataset for global land use/cover mapping with deep learning | Y Benhammou, D Alcaraz-Segura, E Guirado, R Khaldi, B Achchab, .... | 2022 |
| REVEL Framework to measure Local Linear Explanations for black-box models: Deep Learning Image Classification case of study | I Sevillano-García, J Luengo-Martín, F Herrera. | 2022 |
| Una visión actual de la inteligencia artificial: Recorrido histórico, datos y aprendizaje, confiabilidad y datos | MJ del Jesús Díaz, FH Triguero, ÓC García. | 2022 |
| Data harmonisation for information fusion in digital healthcare: A state-of-the-art systematic review, meta-analysis and future research directions | Y Nan, J Del Ser, S Walsh, C Schönlieb, M Roberts, I Selby, K Howard, .... | 2022 |
| Data-driven method to learning personalized individual semantics to support linguistic multi-attribute decision making | CC Li, Y Dong, H Liang, W Pedrycz, F Herrera. | 2022 |
| Mixed opinion dynamics based on DeGroot model and Hegselmann–Krause model in social networks | Z Wu, Q Zhou, Y Dong, J Xu, AH Altalhi, F Herrera. | 2022 |
| Trust-consensus multiplex networks by combining trust social network analysis and consensus evolution methods in group decision-making | T Wu, X Liu, J Qin, F Herrera. | 2022 |
| Replacing pooling functions in Convolutional Neural Networks by linear combinations of increasing functions | I Rodriguez-Martinez, J Lafuente, RHN Santiago, GP Dimuro, F Herrera, .... | 2022 |
| Consensus Convergence Speed in Social Network DeGroot Model: The Effects of the Agents With High Self-Confidence Levels | Z Ding, X Chen, Y Dong, S Yu, F Herrera. | 2022 |
| A framework for adapting online prediction algorithms to outlier detection over time series | A Iturria, J Labaien, S Charramendieta, A Lojo, J Del Ser, F Herrera. | 2022 |
| Managing minority opinions in large-scale group decision making based on community detection and group polarization | T Wu, C Zuheros, X Liu, F Herrera. | 2022 |
| Explanation sets: A general framework for machine learning explainability | RR Fernández, IM de Diego, JM Moguerza, F Herrera. | 2022 |
| Biological behavior of familial papillary thyroid microcarcinoma: Spanish multicenter study | A Ríos, MA Rodríguez, JA Puñal, P Moreno, E Mercader, E Ferrero, .... | 2022 |
| Score Function Based on Concentration Degree for Probabilistic Linguistic Term Sets: An Application to TOPSIS and VIKOR | M Lin, Z Chen, Z Xu, X Gou, F Herrera. | 2021 |
| Revisiting Fuzzy and Linguistic Decision Making: Scenarios and Challenges for Making Wiser Decisions in a Better Way | E Herrera-Viedma, I Palomares, CC Li, FJ Cabrerizo, Y Dong, F Chiclana, .... | 2021 |
| Sentiment Analysis based MpMcDM methodology using NLP and deep learning for smarter decision aid. Case study of restaurant choice using TripAdvisor reviews | C Zuheros, E Martínez-Cámara, E Herrera-Viedma, F Herrera. | 2021 |
| A Tutorial on the Design, Experimentation and Application of Metaheuristic Algorithms to Real-World Optimization Problems | E Osaba, E Villar-Rodriguez, J Del Ser, AJ Nebro, D Molina, A LaTorre, .... | 2021 |
| A panoramic view and swot analysis of artificial intelligence for achieving the sustainable development goals by 2030: progress and prospects | I Palomares, E Martínez-Cámara, R Montes, P García-Moral, M Chiachio, .... | 2021 |
| Integrating Continual Personalized Individual Semantics Learning in Consensus Reaching in Linguistic Group Decision Making | CC Li, Y Dong, W Pedrycz, F Herrera. | 2021 |
| A consensus process based on regret theory with probabilistic linguistic term sets and its application in venture capital | X Tian, Z Xu, J Gu, F Herrera. | 2021 |
| A Practical Tutorial for Decision Tree Induction: Evaluation Measures for Candidate Splits and Opportunities | VAS Hernández, R Monroy, MA Medina-Pérez, O Loyola-González, .... | 2021 |
| An interval type-2 fuzzy Kano-prospect-TOPSIS based QFD model: Application to Chinese e-commerce service design | T Wu, X Liu, J Qin, F Herrera. | 2021 |
| An efficient consensus reaching framework for large-scale social network group decision making and its application in urban resettlement | X Chao, G Kou, Y Peng, E Herrera-Viedma, F Herrera. | 2021 |
| Adaptive Multi-factorial Evolutionary Optimization for Multi-task Reinforcement Learning | AD Martinez, J Del Ser, E Osaba, F Herrera. | 2021 |
| EXplainable Neural-Symbolic Learning (X-NeSyL) methodology to fuse deep learning representations with expert knowledge graphs: the MonuMAI cultural heritage use case | N Díaz-Rodríguez, A Lamas, J Sanchez, G Franchi, I Donadello, S Tabik, .... | 2021 |
| Information fusion for affective computing and sentiment analysis | A Hussain, E Cambria, S Poria, AYA Hawalah, F Herrera. | 2021 |
| A prescription of methodological guidelines for comparing bio-inspired optimization algorithms | A LaTorre, D Molina, E Osaba, J Poyatos, J Del Ser, F Herrera. | 2021 |
| Learning interpretable multi-class models by means of hierarchical decomposition: Threshold Control for Nested Dichotomies | JA Fdez-Sánchez, JD Pascual-Triana, A Fernández, F Herrera. | 2021 |
| Multiple instance classification: Bag noise filtering for negative instance noise cleaning | J Luengo, D Sánchez-Tarragó, RC Prati, F Herrera. | 2021 |
| A tutorial on the segmentation of metallographic images: Taxonomy, new MetalDAM dataset, deep learning-based ensemble model, experimental analysis and challenges | J Luengo, R Moreno, I Sevillano, D Charte, A Peláez-Vegas, .... | 2021 |
| Slicer: Feature Learning for Class Separability with Least-Squares Support Vector Machine Loss and COVID-19 Chest X-Ray Case Study | D Charte, I Sevillano-García, MJ Lucena-González, JL Martín-Rodríguez, .... | 2021 |
| A Preliminary Analysis on Software Frameworks for the Development of Spiking Neural Networks | ÁM García-Vico, F Herrera. | 2021 |
| Distance Metric Learning with Prototype Selection for Imbalanced Classification | JL Suárez, S García, F Herrera. | 2021 |
| A robust approach for deep neural networks in presence of label noise: relabelling and filtering instances during training | A Gómez-Ríos, J Luengo, F Herrera. | 2021 |
| ADOPS: Aspect Discovery OPinion Summarisation Methodology based on deep learning and subgroup discovery for generating explainable opinion summaries | M López, E Martínez-Cámara, MV Luzón, F Herrera. | 2021 |
| Ordinal regression with explainable distance metric learning based on ordered sequences | JL Suárez, S García, F Herrera. | 2021 |
| SOUL: Scala Oversampling and Undersampling Library for imbalance classification | N Rodríguez, D López, A Fernández, S García, F Herrera. | 2021 |
| Special Issue on Methods and Infrastructures for Data Mining at the Edge of Internet of Things | G Fortino, R Buyya, M Chen, F Herrera. | 2021 |
| An indexing algorithm based on clustering of minutia cylinder codes for fast latent fingerprint identification | I Pérez-Sánchez, B Cervantes, MA Medina-Pérez, R Monroy, .... | 2021 |
| Anomaly Detection in Predictive Maintenance: A New Evaluation Framework for Temporal Unsupervised Anomaly Detection Algorithms | J Carrasco, I Markova, D López, I Aguilera, D García, M García-Barzana, .... | 2021 |
| CI-dataset and DetDSCI methodology for detecting too small and too large critical infrastructures in satellite images: Airports and electrical substations as case study | F Pérez-Hernández, J Rodríguez-Ortega, Y Benhammou, F Herrera, .... | 2021 |
| MULTICAST: MULTI Confirmation-level Alarm SysTem based on CNN and LSTM to mitigate false alarms for handgun detection in video-surveillance | R Olmos, S Tabik, F Perez-Hernandez, A Lamas, F Herrera. | 2021 |
| Ordering Artificial Intelligence Based Recommendations to Tackle the SDGs with a Decision-Making Model Based on Surveys | S Alonso, R Montes, D Molina, I Palomares, E Martínez-Cámara, .... | 2021 |
| TimeSpec4LULC: A Global Deep Learning-driven Dataset of MODIS Terra-Aqua Multi-Spectral Time Series for LULC Mapping and Change Detection | R Khaldi, D Alcaraz-Segura, E Guirado, Y Benhammou, A El Afia, .... | 2021 |
| Reducing Data Complexity using Autoencoders with Class-informed Loss Functions | D Charte, F Charte, F Herrera. | 2021 |
| A New Clustering Algorithm With Preference Adjustment Cost to Reduce the Cooperation Complexity in Large-Scale Group Decision Making | T Wu, X Liu, J Qin, F Herrera. | 2021 |
| Sentinel2GlobalLULC: A deep-learning-ready Sentinel-2 RGB image dataset for global land use/cover mapping | DA Segura, E Guirado, R Khaldi, B Achchab, F Herrera, S Tabik. | 2021 |
| A least square support vector machine approach based on bvRNA-GA for modeling photovoltaic systems | X Liu, N Wang, D Molina, F Herrera. | 2021 |
| Editorial: Information fusion for affective computing and sentiment analysis | A Hussain, E Cambria, S Poria, AYA Hawalah, F Herrera. | 2021 |
| More is not Always Better: Insights from a Massive Comparison of Meta-heuristic Algorithms over Real-Parameter Optimization Problems | J Del Ser, E Osaba, AD Martinez, MN Bilbao, J Poyatos, D Molina, .... | 2021 |
| Federated fuzzy learning with imbalanced data | LJ Dust, ML Murcia, A Mäkilä, P Nordin, N Xiong, F Herrera. | 2021 |
| Enhancing the classification of social media opinions by optimizing the structural information | C Vairetti, E Martínez-Cámara, S Maldonado, V Luzón, F Herrera. | 2020 |
| Modeling agent‐based consumers decision‐making with 2‐tuple fuzzy linguistic perceptions | J Giráldez‐Cru, M Chica, O Cordón, F Herrera. | 2020 |
| Numerical Interval Opinion Dynamics with Social Network: Stable State and Consensus | Y Dong, M Zhan, Z Ding, H Liang, F Herrera. | 2020 |
| Dynamic subgroup-quality-based consensus in managing Consistency, Nearness, and Evenness quality indices for large-scale group decision making under hesitant environment | X Gou, H Liao, Z Xu, F Herrera. | 2020 |
| The minimum cost consensus model considering the implicit trust of opinions similarities in social network group decision‐making | T Wu, X Liu, Z Gong, H Zhang, F Herrera. | 2020 |
| Consensus Reaching and Strategic Manipulation in Group Decision Making With Trust Relationships | Y Dong, Q Zha, H Zhang, F Herrera. | 2020 |
| Smart Data based Ensemble for Imbalanced Big Data Classification | D García-Gil, J Holmberg, S García, N Xiong, F Herrera. | 2020 |
| Tree Cover Estimation in Global Drylands from Space Using Deep Learning | E Guirado, D Alcaraz-Segura, J Cabello, S Puertas-Ruíz, F Herrera, .... | 2020 |
| Large-Scale Decision-Making: characterization, taxonomy, challenges and future directions from an Artificial Intelligence and applications perspective | RX Ding, I Palomares, X Wang, GR Yang, B Liu, Y Dong, .... | 2020 |
| A two-step communication opinion dynamics model with self-persistence and influence index for social networks based on the DeGroot model | Q Zhou, Z Wu, AH Altalhi, F Herrera. | 2020 |
| Ensembles of cost-diverse Bayesian neural learners for imbalanced binary classification | M Lázaro, F Herrera, AR Figueiras-Vidal. | 2020 |
| A tutorial on ensembles and deep learning fusion with MNIST as guiding thread: A complex heterogeneous fusion scheme reaching 10 digits error | S Tabik, RF Alvear-Sandoval, MM Ruiz, JL Sancho-Gómez, .... | 2020 |
| Object Detection Binary Classifiers methodology based on deep learning to identify small objects handled similarly: Application in video surveillance | F Pérez-Hernández, S Tabik, A Lamas, R Olmos, H Fujita, F Herrera. | 2020 |
| Recent Trends in the Use of Statistical Tests for Comparing Swarm and Evolutionary Computing Algorithms: Practical Guidelines and a Critical Review | J Castillo, S García, M del Mar Rueda, S Das, F Herrera. | 2020 |
| LUNAR: Cellular Automata for Drifting Data Streams | JL Lobo, J Del Ser, F Herrera. | 2020 |
| Comprehensive Taxonomies of Nature-and Bio-inspired Optimization: Inspiration versus Algorithmic Behavior, Critical Analysis and Recommendations | D Molina, J Poyatos, J Del Ser, S García, A Hussain, F Herrera. | 2020 |
| A Dynamic Credit Index System for TSMEs in China Using the Delphi and Analytic Hierarchy Process (AHP) Methods | A Yu, Z Jia, W Zhang, K Deng, F Herrera. | 2020 |
| Simultaneously Evolving Deep Reinforcement Learning Models using Multifactorial Optimization | AD Martinez, E Osaba, J Del Ser, F Herrera. | 2020 |
| An overview on feedback mechanisms with minimum adjustment or cost in consensus reaching in group decision making: Research paradigms and challenges | H Zhang, S Zhao, G Kou, CC Li, Y Dong, F Herrera. | 2020 |
| Fuzzy k-Nearest Neighbors with monotonicity constraints: Moving towards the robustness of monotonic noise | S González, S García, ST Li, R John, F Herrera. | 2020 |
| Big Data: Technologies and Tools | J Luengo, D García-Gil, S Ramírez-Gallego, S García, F Herrera. | 2020 |
| Smart Data | J Luengo, D García-Gil, S Ramírez-Gallego, S García, F Herrera. | 2020 |
| Imbalanced Data Preprocessing for Big Data | J Luengo, D García-Gil, S Ramírez-Gallego, S García, F Herrera. | 2020 |
| Dimensionality Reduction for Big Data | J Luengo, D García-Gil, S Ramírez-Gallego, S García, F Herrera. | 2020 |
| Data Reduction for Big Data | J Luengo, D García-Gil, S Ramírez-Gallego, S García, F Herrera. | 2020 |
| Big Data Preprocessing: Enabling Smart Data | J Luengo. | 2020 |
| Big Data Preprocessing. Enabling Smart Data; Springer, ISBN 978-3-030-39105-8 | J Luengo, D García-Gil, SG Sergio Ramírez-Gallego, F Herrera. | 2020 |
| Multifactorial Cellular Genetic Algorithm (MFCGA): Algorithmic Design, Performance Comparison and Genetic Transferability Analysis | E Osaba, AD Martinez, JL Lobo, J Del Ser, F Herrera. | 2020 |
| Applications of contemporary decision-making methods to the development of economy and technology | H Liao, Z Xu, H Francisco. | 2020 |
| Fairness in Bio-inspired Optimization Research: A Prescription of Methodological Guidelines for Comparing Meta-heuristics | A LaTorre, D Molina, E Osaba, J Del Ser, F Herrera. | 2020 |
| MNIST-NET10: A heterogeneous deep networks fusion based on the degree of certainty to reach 0.1% error rate. Ensembles overview and proposal | S Tabik, RF Alvear-Sandoval, MM Ruiz, JL Sancho-Gómez, .... | 2020 |
| Redundancy and Complexity Metrics for Big Data Classification: Towards Smart Data | J Maillo, I Triguero, F Herrera. | 2020 |
| Consensus Model Handling Minority Opinions and Noncooperative Behaviors in Large-Scale Group Decision-Making Under Double Hierarchy Linguistic Preference Relations. | X Gou, Z Xu, H Liao, F Herrera. | 2020 |
| An analysis on the use of autoencoders for representation learning: Fundamentals, learning task case studies, explainability and challenges | D Charte, F Charte, MJ del Jesus, F Herrera. | 2020 |
| Tweet Coupling: a social media methodology for clustering scientific publications | SU Hassan, NR Aljohani, M Shabbir, U Ali, S Iqbal, R Sarwar, .... | 2020 |
| Artificial intelligence within the interplay between natural and artificial Computation: advances in data science, trends and applications | JM Górriz, J Ramírez, A Ortíz, FJ Martínez-Murcia, F Segovia, J Suckling, .... | 2020 |
| COVIDGR dataset and COVID-SDNet methodology for predicting COVID-19 based on Chest X-Ray images | S Tabik, A Gómez-Ríos, JL Martín-Rodríguez, I Sevillano-García, .... | 2020 |
| Linguistic Opinions Dynamics based on Personalized Individual Semantics | H Liang, CC Li, Y Dong, F Herrera. | 2020 |
| Irony detection in Twitter with imbalanced class distributions | DIH Farías, R Prati, F Herrera, P Rosso. | 2020 |
| pyDML: A Python Library for Distance Metric Learning | JL Suárez, S García, F Herrera. | 2020 |
| Asynchronous Processing for Latent Fingerprint Identification on Heterogeneous CPU-GPU Systems | AJ Sanchez, LF Romero, D Peralta, MA Medina-Pérez, Y Saeys, .... | 2020 |
| Linguistic group decision making: Axiomatic distance and minimum cost consensus | Y Li, X Chen, Y Dong, F Herrera. | 2020 |
| Federated Learning and Differential Privacy: Software tools analysis, the Sherpa. ai FL framework and methodological guidelines for preserving data privacy | N Rodríguez-Barroso, G Stipcich, D Jiménez-López, JA Ruiz-Millán, .... | 2020 |
| Revisiting Data Complexity Metrics Based on Morphology for Overlap and Imbalance: Snapshot, New Overlap Number of Balls Metrics and Singular Problems Prospect | JD Pascual-Triana, D Charte, MA Arroyo, A Fernández, F Herrera. | 2020 |
| Actas de la XVII Conferencia de la Asociación Española para la Inteligencia Artificial | O Luaces, F Herrera, JA Gámez, L Martínez, E Barrenechea, J Riquelme, .... | 2020 |
| A practical tutorial on bagging and boosting based ensembles for machine learning: Algorithms, software tools, performance study, practical perspectives and opportunities | S González, S García, J Del Ser, L Rokach, F Herrera. | 2020 |
| Revisiting crowd behaviour analysis through deep learning: Taxonomy, anomaly detection, crowd emotions, datasets, opportunities and prospects | FL Sánchez, I Hupont, S Tabik, F Herrera. | 2020 |
| Dynamic Federated Learning Model for Identifying Adversarial Clients | N Rodríguez-Barroso, E Martínez-Cámara, M Luzón, GG Seco, .... | 2020 |
| Distributed Linguistic Representations in Decision Making: Taxonomy, Key Elements and Applications, and Challenges in Data Science and Explainable Artificial Intelligence | Y Wu, Z Zhang, G Kou, H Zhang, X Chao, CC Li, Y Dong, F Herrera. | 2020 |
| Distributed Linguistic Representations in Decision Making: Taxonomy, Key Elements and Applications, and Challenges in Data Science and Explainable Artificial Intelligence | Y Wu, Z Zhang, G Kou, H Zhang, X Chao, CC Li, Y Dong, F Herrera. | 2020 |
| Distributed Linguistic Representations in Decision Making: Taxonomy, Key Elements and Applications, and Challenges in Data Science and Explainable Artificial Intelligence | Y Wu, Z Zhang, G Kou, H Zhang, X Chao, CC Li, Y Dong, F Herrera. | 2020 |
| Sentiment Analysis based Multi-person Multi-criteria Decision Making Methodology: Using Natural Language Processing and Deep Learning for Decision Aid | C Zuheros, E Martínez-Cámara, E Herrera-Viedma, F Herrera. | 2020 |
| Sentiment Analysis based Multi-person Multi-criteria Decision Making Methodology: Using Natural Language Processing and Deep Learning for Decision Aid | C Zuheros, E Martínez-Cámara, E Herrera-Viedma, F Herrera. | 2020 |
| Sentiment Analysis based Multi-person Multi-criteria Decision Making Methodology: Using Natural Language Processing and Deep Learning for Decision Aid | C Zuheros, E Martínez-Cámara, E Herrera-Viedma, F Herrera. | 2020 |
| Lights and Shadows in Evolutionary Deep Learning: Taxonomy, Critical Methodological Analysis, Cases of Study, Learned Lessons, Recommendations and Challenges | AD Martinez, J Del Ser, E Villar-Rodriguez, E Osaba, J Poyatos, S Tabik, .... | 2020 |
| Measuring volatility based on ordered weighted average operators: Agricultural products prices case of use | E León-Castro, LF Espinoza-Audelo, JM Merigó, E Herrera-Viedma, .... | 2020 |
| A novel methodology to classify test cases using natural language processing and imbalanced learning | S Tahvili, L Hatvani, E Ramentol, R Pimentel, W Afzal, F Herrera. | 2020 |
| 2-tuple fuzzy linguistic perceptions and probabilistic awareness-based heuristics for modeling consumer purchase behaviors | J Giráldez-Cru, M Chica, O Cordón, F Herrera. | 2020 |
| Towards Smart Data Technologies for Big Data Analytics | MJ Basgall, M Naiouf, F Herrera, A Fernández. | 2020 |
| HFER: Promoting Explainability in Fuzzy Systems via Hierarchical Fuzzy Exception Rules | JR Trillo, A Fernandez, F Herrera. | 2020 |
| A Tutorial on Distance Metric Learning: Mathematical Foundations, Algorithms, Experimental Analysis, Prospects and Challenges | JL Suárez, S García, F Herrera. | 2020 |
| Incremental learning model inspired in Rehearsal for deep convolutional networks | D Muñoz, C Narváez, C Cobos, M Mendoza, F Herrera. | 2020 |
| Probabilistic double hierarchy linguistic term set and its use in designing an improved VIKOR method: The application in smart healthcare | X Gou, Z Xu, H Liao, F Herrera. | 2020 |
| MonuMAI: Dataset, deep learning pipeline and citizen science based app for monumental heritage taxonomy and classification | A Lamas, S Tabik, P Cruz, R Montes, Á Martínez-Sevilla, T Cruz, .... | 2020 |
| CURIE: A Cellular Automaton for Concept Drift Detection | JL Lobo, J Del Ser, E Osaba, A Bifet, F Herrera. | 2020 |
| AT-MFCGA: An Adaptive Transfer-guided Multifactorial Cellular Genetic Algorithm for Evolutionary Multitasking | E Osaba, J Del Ser, AD Martinez, JL Lobo, F Herrera. | 2020 |
| Fuzzy Logic and Artificial Intelligence: A Special Issue on Emerging Techniques and Their Applications | FY Wang, W Pedrycz, F Herrera, SF Su. | 2020 |
| Distributed Computing and Artificial Intelligence, 16th International Conference | F Herrera, K Matsui, S Rodríguez-González. | 2020 |
| Smart Data driven Decision Trees Ensemble Methodology for Imbalanced Big Data | D García-Gil, S García, N Xiong, F Herrera. | 2020 |
| Dynamic Defense Against Byzantine Poisoning Attacks in Federated Learning | N Rodríguez-Barroso, E Martínez-Cámara, M Luzón, F Herrera. | 2020 |
| Un estudio sobre el preprocesamiento para Redes Neuronales Profundas y Aplicación sobre Reconocimiento de Dígitos Manuscritos | D Peralta, A Herrera, F Herrera. | 2020 |
| Association between chronic lymphocytic thyroiditis and papillary thyroid carcinoma: A retrospective study in surgical specimens | C Osorio, S Ibarra, J Arrieta, M Sarmiento, D Barrios, L Sierra, K Redondo, .... | 2020 |
| Normalidad post-pandemia:¿ una nueva normalidad socioambiental o adiós a la normalidad | D Lew, F Herrera. | 2020 |
| Dealing with difficult minority labels in imbalanced mutilabel data sets | F Charte, AJ Rivera, MJ del Jesus, F Herrera. | 2019 |
| REMEDIAL-HwR: Tackling multilabel imbalance through label decoupling and data resampling hybridization | F Charte, AJ Rivera, MJ del Jesus, F Herrera. | 2019 |
| Ruta: implementations of neural autoencoders in R | D Charte, F Herrera, F Charte. | 2019 |
| Smartdata: data preprocessing to achieve smart data in R | I Cordón, J Luengo, S García, F Herrera, F Charte. | 2019 |
| A Showcase of the Use of Autoencoders in Feature Learning Applications | D Charte, F Charte, MJ del Jesus, F Herrera. | 2019 |
| Evolutionary Fuzzy Systems for Explainable Artificial Intelligence: Why, When, What for, and Where to? | A Fernandez, F Herrera, O Cordon, MJ del Jesus, F Marcelloni. | 2019 |
| Towards Highly Accurate Coral Texture Images Classification Using Deep Convolutional Neural Networks and Data Augmentation | A Gómez-Ríos, S Tabik, J Luengo, ASM Shihavuddin, B Krawczyk, .... | 2019 |
| Brightness guided preprocessing for automatic cold steel weapon detection in surveillance videos with deep learning | A Castillo, S Tabik, F Pérez, R Olmos, F Herrera. | 2019 |
| Detection of Fir Trees (Abies sibirica) Damaged by the Bark Beetle in Unmanned Aerial Vehicle Images with Deep Learning | A Safonova, S Tabik, D Alcaraz-Segura, A Rubtsov, Y Maglinets, .... | 2019 |
| Deep recurrent neural network for geographical entities disambiguation on social media data | C Zuheros, S Tabik, A Valdivia, E Martínez-Cámara, F Herrera. | 2019 |
| Redes Neuronales Convolucionales para Una Clasificacion Precisa de Imágenes de Corales | A Gómez-Rıos, S Tabik, J Luengo, F Herrera, ASM Shihavuddin, .... | 2019 |
| Enabling smart data: noise filtering in big data classification | D García-Gil, J Luengo, S García, F Herrera. | 2019 |
| Emerging topics and challenges of learning from noisy data in nonstandard classification: a survey beyond binary class noise | RC Prati, J Luengo, F Herrera. | 2019 |
| E2SAM: Evolutionary Ensemble of Sentiment Analysis Methods for Domain Adaptation | M López, A Valdivia, E Martínez-Cámara, MV Luzón, F Herrera. | 2019 |
| A multi-objective evolutionary fuzzy system to obtain a broad and accurate set of solutions in intrusion detection systems | S Elhag, A Fernández, A Altalhi, S Alshomrani, F Herrera. | 2019 |
| Bio-inspired computation: Where we stand and what's next | J Del Ser, E Osaba, D Molina, XS Yang, S Salcedo-Sanz, D Camacho, .... | 2019 |
| Analysis of self‐confidence indices‐based additive consistency for fuzzy preference relations with self‐confidence and its application in group decision making | X Liu, Y Xu, R Montes, Y Dong, F Herrera. | 2019 |
| A Novel Memetic Framework for Enhancing Differential Evolution Algorithms via Combination With Alopex Local Search | M Leon, N Xiong, D Molina, F Herrera. | 2019 |
| An overview on managing additive consistency of reciprocal preference relations for consistency-driven decision making and fusion: Taxonomy and future directions | CC Li, Y Dong, Y Xu, F Chiclana, E Herrera-Viedma, F Herrera. | 2019 |
| Instance reduction for one-class classification | B Krawczyk, I Triguero, S García, M Woźniak, F Herrera. | 2019 |
| Chain based sampling for monotonic imbalanced classification | S González, S García, ST Li, F Herrera. | 2019 |
| A consensus model for large-scale linguistic group decision making with a feedback recommendation based on clustered personalized individual semantics and opposing consensus groups | CC Li, Y Dong, F Herrera. | 2019 |
| DPASF: a flink library for streaming data preprocessing | A Alcalde-Barros, D García-Gil, S García, F Herrera. | 2019 |
| Score-HeDLiSF: A score function of hesitant fuzzy linguistic term set based on hesitant degrees and linguistic scale functions: An application to unbalanced hesitant fuzzy … | H Liao, R Qin, C Gao, X Wu, A Hafezalkotob, F Herrera. | 2019 |
| An overview of MULTIMOORA for multi-criteria decision-making: Theory, developments, applications, and challenges | A Hafezalkotob, A Hafezalkotob, H Liao, F Herrera. | 2019 |
| Visualizing and rectifying different inconsistencies for fuzzy reciprocal preference relations | Y Xu, F Herrera. | 2019 |
| Consensus model for large-scale group decision making based on fuzzy preference relation with self-confidence: Detecting and managing overconfidence behaviors | X Liu, Y Xu, F Herrera. | 2019 |
| Large-scale group decision making model based on social network analysis: trust relationship-based conflict detection and elimination | B Liu, Q Zhou, RX Ding, I Palomares, F Herrera. | 2019 |
| Sparse Representation-Based Intuitionistic Fuzzy Clustering Approach to Find the Group Intra-Relations and Group Leaders for Large-Scale Decision Making | R Ding, X Wang, K Shang, B Liu, F Herrera. | 2019 |
| Revisiting inconsistent judgements for incomplete fuzzy linguistic preference relations: Algorithms to identify and rectify ordinal inconsistencies | Y Xu, F Ma, F Herrera. | 2019 |
| An integrated method for cognitive complex multiple experts multiple criteria decision making based on ELECTRE III with weighted Borda rule | H Liao, X Wu, X Mi, F Herrera. | 2019 |
| Interval MULTIMOORA Method Integrating Interval Borda Rule and Interval Best-Worst-Method-Based Weighting Model: Case Study on Hybrid Vehicle Engine Selection | A Hafezalkotob, A Hafezalkotob, H Liao, F Herrera. | 2019 |
| Transforming Big Data into Smart Data: An insight on the use of k-Nearest Neighbours algorithm to obtain quality data | I Triguero, J Maillo, D García, J Luengo, S García, F Herrera. | 2019 |
| A Group Decision Making Approach Considering Self-confidence Behaviors and Its Application in Environmental Pollution Emergency Management | X Liu, Y Xu, Y Ge, W Zhang, F Herrera. | 2019 |
| Generic Disjunctive Belief Rule Base Modeling, Inferencing, and Optimization | LL Chang, ZJ Zhou, H Liao, Y Chen, X Tan, F Herrera. | 2019 |
| Group Decision Making with Double Hierarchy Hesitant Fuzzy Linguistic Preference Relations: Consistency based Measures, Index and Repairing Algorithms and Decision Model | X Gou, H Liao, Z Xu, R Min, F Herrera. | 2019 |
| Consensus Reaching in Social Network DeGroot Model: The Roles of the Self-confidence and Node Degree | Z Ding, X Chen, Y Dong, F Herrera. | 2019 |
| Ordinal consensus measure with objective threshold for heterogeneous large-scale group decision making | M Tang, X Zhou, H Liao, J Xu, H Fujita, F Herrera. | 2019 |
| Consensus Evolution Networks: A Consensus Reaching tool for Managing Consensus Thresholds in Group Decision Making | T Wu, X Liu, J Qin, F Herrera. | 2019 |
| Virtual learning environment to predict withdrawal by leveraging deep learning | SU Hassan, H Waheed, NR Aljohani, M Ali, S Ventura, F Herrera. | 2019 |
| Analyze, Sense, Preprocess, Predict, Implement, and Deploy (ASPPID): An incremental methodology based on data analytics for cost-efficiently monitoring the industry 4.0 | J Para, J Del Ser, AJ Nebro, U Zurutuza, F Herrera. | 2019 |
| A Meta-Hierarchical Rule Decision System to Design Robust Fuzzy Classifiers Based on Data Complexity | JC del Olmo, A Fernandez, F Herrera, J Gamez. | 2019 |
| Life satisfaction evaluation in earthquake-hit area by the probabilistic linguistic GLDS method integrated with the logarithm-multiplicative analytic hierarchy process | H Liao, J Yu, X Wu, A Al-Barakati, A Altalhi, F Herrera. | 2019 |
| The Inconsistencies on TripAdvisor Reviews: a Unified Index between Users and Sentiment Analysis Methods | A Valdivia, E Hrabova, I Chaturvedi, MV Luzón, L Troiano, E Cambria, .... | 2019 |
| A Review of Fingerprint Feature Representations and Their Applications for Latent Fingerprint Identification: Trends and Evaluation | D Valdes-Ramirez, MA Medina-Pérez, R Monroy, O Loyola-González, .... | 2019 |
| Hesitant Fuzzy Linguistic Analytic Hierarchical Process With Prioritization, Consistency Checking, and Inconsistency Repairing | X Mi, X Wu, M Tang, H Liao, A Al-Barakati, AH Altalhi, F Herrera. | 2019 |
| Social Network Analysis-Based Conflict Relationship Investigation and Conflict Degree-based Consensus Reaching Process for Large Scale Decision Making Using Sparse Representation | RX Ding, X Wang, K Shang, F Herrera. | 2019 |
| Special Issue on Hybrid Artificial Intelligence Systems from the HAIS 2017 Conference–Editorial | FJM de Pisón Ascacíbar, F Herrera, A Abraham, M Wozniak, E Corchado. | 2019 |
| An Analysis of Local and Global Solutions to Address Big Data Imbalanced Classification: A Case Study with SMOTE Preprocessing | MJ Basgall, W Hasperué, M Naiouf, A Fernández, F Herrera. | 2019 |
| Coral species identification with texture or structure images using a two-level classifier based on Convolutional Neural Networks | A Gómez-Ríos, S Tabik, J Luengo, ASM Shihavuddin, F Herrera. | 2019 |
| Deep Learning in Video Multi-Object Tracking: A Survey | G Ciaparrone, FL Sánchez, S Tabik, L Troiano, R Tagliaferri, F Herrera. | 2019 |
| Applying Memetic algorithm with Improved L-SHADE and Local Search Pool for the 100-digit challenge on Single Objective Numerical Optimization | D Molina, F Herrera. | 2019 |
| Hesitancy degree-based correlation measures for hesitant fuzzy linguistic term sets and their applications in multiple criteria decision making | H Liao, X Gou, Z Xu, XJ Zeng, F Herrera. | 2019 |
| Consensus based on multiplicative consistent double hierarchy linguistic preferences: Venture capital in real estate market | X Gou, H Liao, X Wang, Z Xu, F Herrera. | 2019 |
| Fast and Scalable Approaches to Accelerate the Fuzzy k Nearest Neighbors Classifier for Big Data | J Maillo, I Triguero, J Luengo, FH S. García. | 2019 |
| Defective alternatives detection-based multi-attribute intuitionistic fuzzy large-scale decision making model | B Liu, Q Zhou, RX Ding, W Ni, F Herrera. | 2019 |
| A First Approach on Big Data Missing Values Imputation | B Montesdeoca, J Luengo, J Maillo, D García-Gil, S García, F Herrera. | 2019 |
| otsad: A Package for Online Time-Series Anomaly Detectors | A Iturria, J Carrasco, S Charramendieta, A Conde, F Herrera. | 2019 |
| From Big to Smart Data: Iterative Ensemble Filter for Noise Filtering in Big Data classification | FH Diego Garcia, Francisco Luque-Sánchez, Julián Luengo, Salvador García. | 2019 |
| BreakHis based Breast Cancer Automatic Diagnosis using Deep Learning: Taxonomy, Survey and Insights | Y Benhammou, B Achchab, F Herrera, S Tabik. | 2019 |
| Whale counting in satellite and aerial images with deep learning | E Guirado, S Tabik, ML Rivas, D Alcaraz-Segura, F Herrera. | 2019 |
| Guest Editorial: Computational Intelligence for Big Data Analytics | A Fernandez, I Triguero, M Galar, F Herrera. | 2019 |
| Deep Learning Hyper-parameter Tuning for Sentiment Analysis in Twitter based on Evolutionary Algorithms | N Rodríguez-Barroso, AR Moya, JA Fernández, E Romero, .... | 2019 |
| Overview of Hesitant Linguistic Preference Relations for Representing Cognitive Complex Information: Where We Stand and What Is Next | H Liao, M Tang, R Qin, X Mi, A Altalhi, S Alshomrani, F Herrera. | 2019 |
| Overview of Hesitant Linguistic Preference Relations for Representing Cognitive Complex Information: Where We Stand and What Is Next | H Liao, M Tang, R Qin, X Mi, A Altalhi, S Alshomrani, F Herrera. | 2019 |
| Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI | AB Arrieta, N Díaz-Rodríguez, J Del Ser, A Bennetot, S Tabik, A Barbado, .... | 2019 |
| Preprocessing methodology for time series: an industrial world application case study | JA Cortés-Ibáñez, S González, JJ Valle-Alonso, J Luengo, S García, .... | 2019 |
| Deep Learning in Omics Data Analysis and Precision Medicine | J Martorell-Marugán, S Tabik, Y Benhammou, C del Val, I Zwir, F Herrera, .... | 2019 |
| Special Issue SOCO 2017: New trends in soft computing and its application in industrial and environmental problems | F Herrera, A Abraham, M Wózniak, H Peréz, E Corchado. | 2019 |
| Balance Dynamic Clustering Analysis and Consensus Reaching Process with Consensus Evolution Networks in Large-scale Group Decision Making | T Wu, X Liu, J Qin, F Herrera. | 2019 |
| Big Data Preprocessing as the Bridge between Big Data and Smart Data: BigDaPSpark and BigDaPFlink Libraries | D Garcıa-Gil, A Alcalde-Barros, J Luengo, S Garcıa, F Herrera. | 2019 |
| Predicting literature’s early impact with sentiment analysis in Twitter | SU Hassan, NR Aljohani, N Idrees, R Sarwar, R Nawaz, .... | 2019 |
| Decision making model based on expert evaluations extracted with sentiment analysis | C Zuheros, E Martínez-Cámara, E Herrera-Viedma, F Herrera. | 2019 |
| A Review of Fingerprint Feature Representations and Their Applications for Latent Fingerprint Identification: Trends and Evaluation. | D Valdes-Ramirez, MA Medina-Pérez, R Monroy, O Loyola-González, .... | 2019 |
| Evolutionary fuzzy systems: a case study for intrusion detection systems | S Elhag, A Fernández, S Alshomrani, F Herrera. | 2019 |
| decision making: Managing self-confidence-based consensus model with the dynamic importance degree of experts and trust-based feedback mechanism | X Liu, Y Xu, R Montes, F Herrera, Social network group. | 2019 |
| Social network group decision making: Managing self-confidence-based consensus models with the dynamic importance degree of experts and trust-based feedback mechanism | X Liu, Y Xu, R Montes, F Herrera. | 2019 |
| Springer: Cham | F Herrera, K Matsui, S Rodríguez-González. | 2019 |
| La investigación educacional: una vía para elevar la calidad educativa | J Fiallo, J Cerezal, S Jiménez, F Herrera, Y Hedesa. | 2019 |
| A unifying analysis for the supervised descriptive rule discovery via the weighted relative accuracy | CJ Carmona, MJ del Jesus, F Herrera. | 2018 |
| A practical tutorial on autoencoders for nonlinear feature fusion: Taxonomy, models, software and guidelines | D Charte, F Charte, S García, MJ del Jesus, F Herrera. | 2018 |
| A snapshot on nonstandard supervised learning problems: taxonomy, relationships, problem transformations and algorithm adaptations | D Charte, F Charte, S García, F Herrera. | 2018 |
| Tips, guidelines and tools for managing multi-label datasets: The mldr. datasets R package and the Cometa data repository | F Charte, AJ Rivera, D Charte, MJ del Jesus, F Herrera. | 2018 |
| Automatic Handgun Detection Alarm in Videos Using Deep Learning | R Olmos, S Tabik, F Herrera. | 2018 |
| A Binocular Image Fusion Approach for Minimizing False Positives in Handgun Detection with Deep Learning | R Olmos, S Tabik, A Castillo, F Pérez, F Herrera. | 2018 |
| A first study exploring the performance of the state-of-the art CNN model in the problem of breast cancer | Y Benhammou, S Tabik, B Achchab, F Herrera. | 2018 |
| Framework for the Training of Deep Neural Networks in TensorFlow Using Metaheuristics | J Muñoz-Ordóñez, C Cobos, M Mendoza, E Herrera-Viedma, F Herrera, .... | 2018 |
| A First Step to Accelerating Fingerprint Matching Based on Deformable Minutiae Clustering | AJ Sanchez, LF Romero, S Tabik, MA Medina-Pérez, F Herrera. | 2018 |
| XVIII Conferencia de la Asociación Española para la Inteligencia Artificial (CAEPIA 2018) | JDELSER FRANCISCO HERRERA, SERGIO DAMAS, ROSANA MONTES, SERGIO ALONSO .... | 2018 |
| Automatic whale counting in satellite images with deep learning | E Guirado, S Tabik, ML Rivas, D Alcaraz-Segura, F Herrera. | 2018 |
| Personalized individual semantics based on consistency in hesitant linguistic group decision making with comparative linguistic expressions | CC Li, RM Rodríguez, L Martínez, Y Dong, F Herrera. | 2018 |
| Consistency of hesitant fuzzy linguistic preference relations: An interval consistency index | CC Li, RM Rodríguez, L Martínez, Y Dong, F Herrera. | 2018 |
| CNC-NOS: Class noise cleaning by ensemble filtering and noise scoring | J Luengo, SO Shim, S Alshomrani, A Altalhi, F Herrera. | 2018 |
| A preliminary study on Hybrid Spill-Tree Fuzzy k-Nearest Neighbors for big data classification | J Maillo, J Luengo, S García, F Herrera, I Triguero. | 2018 |
| Consensus building with individual consistency control in group decision making | CC Li, RM Rodríguez, L Martínez, Y Dong, F Herrera. | 2018 |
| A First Study on the Use of Noise Filtering to Clean the Bags in Multi-Instance Classification | J Luengo, D Sánchez-Tarragó, RC Prati, F Herrera. | 2018 |
| MRQAR: a generic MapReduce framework to discover Quantitative Association Rules in Big Data problems | D Martin, M Martinez-Ballesteros, D Garcia-Gil, J Alcala-Fdez, .... | 2018 |
| Computing with words: Revisiting the qualitative scale | C Zuheros, CC Li, FJ Cabrerizo, Y Dong, E Herrera-Viedma, F Herrera. | 2018 |
| On the use of convolutional neural networks for robust classification of multiple fingerprint captures | D Peralta, I Triguero, S García, Y Saeys, JM Benitez, F Herrera. | 2018 |
| A distributed evolutionary multivariate discretizer for big data processing on apache spark | S Ramírez-Gallego, S García, JM Benítez, F Herrera. | 2018 |
| Big data: Tutorial and guidelines on information and process fusion for analytics algorithms with MapReduce | S Ramírez-Gallego, A Fernández, S García, M Chen, F Herrera. | 2018 |
| Dynamic affinity-based classification of multi-class imbalanced data with one-versus-one decomposition: a fuzzy rough set approach | S Vluymans, A Fernández, Y Saeys, C Cornelis, F Herrera. | 2018 |
| Resumiendo Opiniones Negativas con Deep Learning y Reglas Descriptivas | A Valdivia, E Martínez-Cámara, MV Luzón, F Herrera. | 2018 |
| Imbalance: oversampling algorithms for imbalanced classification in R | I Cordón, S García, A Fernández, F Herrera. | 2018 |
| What do people think about this monument? Understanding negative reviews via deep learning, clustering and descriptive rules | A Valdivia, E Martínez-Cámara, I Chaturvedi, MV Luzón, E Cambria, .... | 2018 |
| Consensus vote models for detecting and filtering neutrality in sentiment analysis | A Valdivia, MV Luzón, E Cambria, F Herrera. | 2018 |
| An insight into bio-inspired and evolutionary algorithms for global optimization: review, analysis, and lessons learnt over a decade of competitions | D Molina, A LaTorre, F Herrera. | 2018 |
| Alternative ranking-based clustering and reliability index-based consensus reaching process for hesitant fuzzy large scale group decision making | X Liu, Y Xu, R Montes, RX Ding, F Herrera. | 2018 |
| Teranga Go!: Carpooling Collaborative Consumption Community with multi-criteria hesitant fuzzy linguistic term set opinions to build confidence and trust | R Montes, AM Sanchez, P Villar, F Herrera. | 2018 |
| SHADE with iterative local search for large-scale global optimization | D Molina, A LaTorre, F Herrera. | 2018 |
| The use of fuzzy linguistic information and Fuzzy Delphi method to validate by consensus a questionnaire in a Blended-Learning environment | J Morales, R Montes, N Zermeño, J Duran, F Herrera. | 2018 |
| Hesitant fuzzy linguistic term set and its application in decision making: a state-of-the-art survey | H Liao, Z Xu, E Herrera-Viedma, F Herrera. | 2018 |
| SMOTE for Learning from Imbalanced Data: Progress and Challenges. Marking the 15-year Anniversary | A Fernández, S Garcıa, F Herrera, NV Chawla. | 2018 |
| Dynamic ensemble selection for multi-class imbalanced datasets | S García, ZL Zhang, A Altalhi, S Alshomrani, F Herrera. | 2018 |
| Learning from Imbalanced Data Sets | A Fernández, S García, M Galar, RC Prati, B Krawczyk, F Herrera. | 2018 |
| Principal components analysis random discretization ensemble for big data | D García-Gil, S Ramírez-Gallego, S García, F Herrera. | 2018 |
| Distinguishing Between Facts and Opinions for Sentiment Analysis: Survey and Challenges | I Chaturvedi, E Cambria, RE Welsch, F Herrera. | 2018 |
| DRCW-ASEG: One-versus-One distance-based relative competence weighting with adaptive synthetic example generation for multi-class imbalanced datasets | ZL Zhang, XG Luo, S González, S García, F Herrera. | 2018 |
| Mc2esvm: multiclass classification based on cooperative evolution of support vector machines | A Rosales-Pérez, S García, H Terashima-Marin, CAC Coello, F Herrera. | 2018 |
| Cognitive Computing: Human-Centered Computing with Cognitive Intelligence on Clouds | M Chen, F Herrera, K Hwang. | 2018 |
| Online entropy-based discretization for data streaming classification | S Ramírez-Gallego, S García, F Herrera. | 2018 |
| Probabilistic Linguistic MULTIMOORA: A Multi-Criteria Decision Making Method Based on the Probabilistic Linguistic Expectation Function and the Improved Borda Rule | X Wu, H Liao, Z Xu, A Hafezalkotob, F Herrera. | 2018 |
| A Tutorial on Distance Metric Learning: Mathematical Foundations, Algorithms and Software | JL Suárez, S García, F Herrera. | 2018 |
| OCAPIS: R package for Ordinal Classification and Preprocessing in Scala | MC Heredia-Gómez, S García, PA Gutiérrez, F Herrera. | 2018 |
| Cooperative multi-objective evolutionary support vector machines for multiclass problems | A Rosales-Pérez, AE Gutierrez-Rodríguez, S García, H Terashima-Marín, .... | 2018 |
| On the Use of Random Discretization and Dimensionality Reduction in Ensembles for Big Data | D García-Gil, S Ramírez-Gallego, S García, F Herrera. | 2018 |
| BELIEF: A distance-based redundancy-proof feature selection method for Big Data | S Ramírez-Gallego, S García, N Xiong, F Herrera. | 2018 |
| Consensus Reaching Process for Large-scale Group Decision Making with Double Hierarchy Hesitant Fuzzy Linguistic Preference Relations | X Gou, Z Xu, F Herrera. | 2018 |
| Intuitionistic fuzzy analytic network process | HC Liao, XM Mi, ZS Xu, JP Xu, F Herrera. | 2018 |
| Mining association rules on Big Data through MapReduce genetic programming | F Padillo, JM Luna, F Herrera, S Ventura. | 2018 |
| A new hesitant fuzzy linguistic ORESTE method for hybrid multi-criteria decision making | HC Liao, XL Wu, XD Liang, JP Xu, F Herrera. | 2018 |
| A continuous interval-valued linguistic ORESTE method for multi-criteria group decision making | H Liao, X Wu, X Liang, JB Yang, DL Xu, F Herrera. | 2018 |
| A multi-objective evolutionary approach to training set selection for support vector machine | G Acampora, F Herrera, G Tortora, A Vitiello. | 2018 |
| Multi-Label Classification using a Fuzzy Rough Neighborhood Consensus | S Vluymans, C Cornelis, F Herrera, Y Saeys. | 2018 |
| Dynamic ensemble selection for multi-class classification with one-class classifiers | B Krawczyk, M Galar, M Woźniak, H Bustince, F Herrera. | 2018 |
| Multiple Criteria Decision Making based on Distance and Similarity Measures under Double Hierarchy Hesitant Fuzzy Linguistic environment | X Gou, Z Xu, H Liao, F Herrera. | 2018 |
| Exploring Consistency for Hesitant Preference Relations in Decision Making: Discussing Concepts, Meaning and Taxonomy | RM Rodriguez, Y Xu, L Martinez, F Herrera. | 2018 |
| Underground mining method selection with the hesitant fuzzy linguistic gained and lost dominance score method | Z Fu, X Wu, H Liao, F Herrera. | 2018 |
| Surveying alignment-free features for Ortholog detection in related yeast proteomes by using supervised big data classifiers | D Galpert, A Fernández, F Herrera, A Antunes, R Molina-Ruiz, .... | 2018 |
| On a new methodology for ranking fuzzy numbers and its application to real economic data | A Roldan, C Roldán, F Herrera. | 2018 |
| DNBMA: A Double Normalization-Based Multi-Aggregation Method | H Liao, X Wu, F Herrera. | 2018 |
| SMOTE-BD: An Exact and Scalable Oversampling Method for Imbalanced Classification in Big Data | MJ Basgall, W Hasperué, M Naiouf, A Fernández, F Herrera. | 2018 |
| Editorial Message: Special Issue on Hesitant Fuzzy Linguistic Decision Making: Algorithms, Theory and Applications | H Liao, Z Xu, F Herrera, JM Merigó. | 2018 |
| A Preliminary Study of the Feasibility of Global Evolutionary Feature Selection for Big Datasets under Apache Spark | M Galar, I Triguero, H Bustince, F Herrera. | 2018 |
| Cost-sensitive learning | A Fernández, S García, M Galar, RC Prati, B Krawczyk, F Herrera. | 2018 |
| Imbalanced Classification for Big Data | A Fernández, S García, M Galar, RC Prati, B Krawczyk, F Herrera. | 2018 |
| Learning from Imbalanced Data Streams | A Fernández, S García, M Galar, RC Prati, B Krawczyk, F Herrera. | 2018 |
| Data Intrinsic Characteristics | A Fernández, S García, M Galar, RC Prati, B Krawczyk, F Herrera. | 2018 |
| Performance measures | A Fernández, S García, M Galar, RC Prati, B Krawczyk, F Herrera. | 2018 |
| Ensemble learning | A Fernández, S García, M Galar, RC Prati, B Krawczyk, F Herrera. | 2018 |
| Algorithm-Level Approaches | A Fernández, S García, M Galar, RC Prati, B Krawczyk, F Herrera. | 2018 |
| Data Level Preprocessing Methods | A Fernández, S García, M Galar, RC Prati, B Krawczyk, F Herrera. | 2018 |
| Imbalanced Classification with Multiple Classes | A Fernández, S García, M Galar, RC Prati, B Krawczyk, F Herrera. | 2018 |
| Introduction to KDD and Data Science | A Fernández, S García, M Galar, RC Prati, B Krawczyk, F Herrera. | 2018 |
| Dimensionality Reduction for Imbalanced Learning | A Fernández, S García, M Galar, RC Prati, B Krawczyk, F Herrera. | 2018 |
| Foundations on Imbalanced Classification | A Fernández, S García, M Galar, RC Prati, B Krawczyk, F Herrera. | 2018 |
| Red Neural Recurrente para la Desambiguacion de Entidades en Datos de Medios Sociales | C Zuheros, S Tabik, A Valdivia, E Martınez-Cámara, F Herrera. | 2018 |
| k-Vecinos más Cercanos Difuso para Clasificación Monotónica | S González, S García, ST Li, R John, F Herrera. | 2018 |
| Un enfoque aproximado para acelerar el algoritmo de clasificacion Fuzzy kNN para Big Data | J Maillo, J Luengo, S Garcıa, F Herrera, I Triguero. | 2018 |
| Bagging-RandomMiner-Un Algoritmo en MapReduce para Deteccion de Anomalıas en Big Data | L Pereyra, D Garcıa-Gil, F Herrera, LC González-Gurrola, J Carrasco, .... | 2018 |
| A Tutorial on Distance Metric Learning: Mathematical Foundations, Algorithms and Experiments | JL Suárez, S García, F Herrera. | 2018 |
| An insight into evolutionary algorithms for continuous optimization: learning by competitions | D Molina, AL de la Fuente, F Herrera. | 2018 |
| SHADE con búsqueda local iterativa para optimización global de alta dimensionalidad | D Molina, AL de la Fuente, F Herrera. | 2018 |
| Evaluacion de estrategias de binarizacion en la clasificacion de imágenes usando deep learning | F Pérez, S Tabik, A Castillo, H Fujita, F Herrera. | 2018 |
| Competicion CAEPIA-App: MonuMAI, una app para incrementar el valor social del patrimonio-arquitectonico andaluz | F Herrera, A Martinez-Sevilla, S Tabik, R Montes, A Castillo, TC Sánchez, .... | 2018 |
| Preprocesamiento guiado por luminosidad para la deteccion automática de armas blancas en video vigilancia con Deep Learning | A Castillo, S Tabik, F Pérez, R Olmos, F Herrera. | 2018 |
| NMC, Nearest Matrix Classification: A new combination model for pruning one-vs-one ensembles by transforming the aggregation problem | MG Idoate, A Fernández, EB Tartas, HB Sola, F Herrera. | 2018 |
| Deteccion del Fracaso Académico y Evaluacion de la Práctica Docente mediante la Comunicacion Automatizada con un Chatbot | JM Morales, R Montes, F Herrera. | 2018 |
| Modelo de evaluacion de la usabilidad de entornos web basado en las metodologıas de computing with words y design thinking. Caso de uso en entornos virtuales de aprendizaje | N Zermeno, R Montes, F Herrera. | 2018 |
| Toma de decisiones a gran escala usando evaluacion parcial de criterios. Caso aplicado a evaluacion de conferencias | J Duran, R Montes, F Herrera. | 2018 |
| Fuzzy linguistic ranking model for Web Accessibility Test tools | N Zermeno, LDDR Calache, R Montes, F Herrera. | 2018 |
| Advances in Artificial Intelligence: 18th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2018, Granada, Spain, October 23–26, 2018, Proceedings | F Herrera, S Damas, R Montes, S Alonso, Ó Cordón, A González, .... | 2018 |
| Smart Data: Filtrado de Ruido para Big Data | DJG Gil, J Luengo, SG Gil, F Herrera. | 2018 |
| A geometrical robust design using the Taguchi method: application to a fatigue analysis of a right angle bracket | R Barea, S Novoa, F Herrera, B Achiaga, N Candela. | 2018 |
| Advances in Artificial Intelligence | F Herrera, S Damas, R Montes, S Alonso, Ó Cordón, A González, .... | 2018 |
| A first approach towards a fuzzy decision tree for multilabel classification | RC Prati, F Charte, F Herrera. | 2017 |
| KEEL 3.0: an open source software for multi-stage analysis in data mining | I Triguero, S González, JM Moyano, S García López, J Alcalá Fernández, .... | 2017 |
| Deep-learning versus OBIA for scattered shrub detection with Google Earth imagery: Ziziphus lotus as case study | E Guirado, S Tabik, D Alcaraz-Segura, J Cabello, F Herrera. | 2017 |
| A snapshot of image pre-processing for convolutional neural networks: case study of MNIST | S Tabik, D Peralta, A Herrera-Poyatos, F Herrera. | 2017 |
| Personalized individual semantics in computing with words for supporting linguistic group decision making. An application on consensus reaching | CC Li, Y Dong, F Herrera, E Herrera-Viedma, L Martínez. | 2017 |
| Managing consensus based on leadership in opinion dynamics | Y Dong, Z Ding, L Martínez, F Herrera. | 2017 |
| Exact fuzzy k-nearest neighbor classification for big datasets | J Maillo, J Luengo, S García, F Herrera, I Triguero. | 2017 |
| A study on the noise label influence in boosting algorithms: AdaBoost, GBM and XGBoost | A Gómez-Ríos, J Luengo, F Herrera. | 2017 |
| The noisefiltersr package: label noise preprocessing in R | P Morales, J Luengo, LPF Garcia, AC Lorena, AC de Carvalho, F Herrera. | 2017 |
| A consistency-driven approach to set personalized numerical scales for hesitant fuzzy linguistic preference relations | CC Li, RM Rodríguez, F Herrera, L Martinez, Y Dong. | 2017 |
| Fast‐mRMR: Fast Minimum Redundancy Maximum Relevance Algorithm for High‐Dimensional Big Data | S Ramírez‐Gallego, I Lastra, D Martínez‐Rego, V Bolón‐Canedo, .... | 2017 |
| An information theory-based feature selection framework for big data under apache spark | S Ramírez-Gallego, H Mouriño-Talín, D Martínez-Rego, V Bolón-Canedo, .... | 2017 |
| Nearest neighbor classification for high-speed big data streams using spark | S Ramírez-Gallego, B Krawczyk, S García, M Woźniak, JM Benítez, .... | 2017 |
| Minutiae-based fingerprint matching decomposition: methodology for big data frameworks | D Peralta, S García, JM Benitez, F Herrera. | 2017 |
| Distributed incremental fingerprint identification with reduced database penetration rate using a hierarchical classification based on feature fusion and selection | D Peralta, I Triguero, S García, Y Saeys, JM Benitez, F Herrera. | 2017 |
| SMOTE-GPU: Big data preprocessing on commodity hardware for imbalanced classification | PD Gutiérrez, M Lastra, JM Benítez, F Herrera. | 2017 |
| Robust classification of different fingerprint copies with deep neural networks for database penetration rate reduction | D Peralta, I Triguero, S García, Y Saeys, JM Benitez, F Herrera. | 2017 |
| An insight into imbalanced Big Data classification: outcomes and challenges | A Fernández, S del Río, NV Chawla, F Herrera. | 2017 |
| Fuzzy rule based classification systems for big data with MapReduce: granularity analysis | A Fernández, S del Río, A Bawakid, F Herrera. | 2017 |
| NMC: nearest matrix classification–A new combination model for pruning One-vs-One ensembles by transforming the aggregation problem | M Galar, A Fernández, E Barrenechea, H Bustince, F Herrera. | 2017 |
| Why Linguistic Fuzzy Rule Based Classification Systems perform well in Big Data Applications? | A Fernández, S Alshomrani, A Altalhi, F Herrera. | 2017 |
| GPU Processing for Biometric Big Data Based Identification. Why and what for? | M Lastra, PD Gutiérrez, JM Benítez, F Herrera. | 2017 |
| Sentiment analysis in tripadvisor | A Valdivia, MV Luzón, F Herrera. | 2017 |
| Sentiment Analysis on TripAdvisor: Are There Inconsistencies in User Reviews? | A Valdivia, MV Luzón, F Herrera. | 2017 |
| Since CEC 2005 competition on real-parameter optimisation: a decade of research, progress and comparative analysis’s weakness | C García-Martínez, PD Gutiérrez, D Molina, M Lozano, F Herrera. | 2017 |
| Analysis among winners of different IEEE CEC competitions on real-parameters optimization: Is there always improvement? | D Molina, F Moreno-García, F Herrera. | 2017 |
| A decision making model to evaluate the reputation in social networks using HFLTS | R Montes, AM Sanchez, P Villar, F Herrera. | 2017 |
| kNN-IS: An Iterative Spark-based design of the k-Nearest Neighbors classifier for big data | J Maillo, S Ramírez, I Triguero, F Herrera. | 2017 |
| A survey on data preprocessing for data stream mining: Current status and future directions | S Ramírez-Gallego, B Krawczyk, S García, M Woźniak, F Herrera. | 2017 |
| Double hierarchy hesitant fuzzy linguistic term set and MULTIMOORA method: A case of study to evaluate the implementation status of haze controlling measures | X Gou, H Liao, Z Xu, F Herrera. | 2017 |
| A comparison on scalability for batch big data processing on Apache Spark and Apache Flink | D García-Gil, S Ramírez-Gallego, S García, F Herrera. | 2017 |
| Class switching according to nearest enemy distance for learning from highly imbalanced data-sets | S Gónzalez, S García, M Lázaro, AR Figueiras-Vidal, F Herrera. | 2017 |
| Exploring the effectiveness of dynamic ensemble selection in the one-versus-one scheme | ZL Zhang, XG Luo, S García, JF Tang, F Herrera. | 2017 |
| A linear programming method for multiple criteria decision making with probabilistic linguistic information | H Liao, L Jiang, Z Xu, J Xu, F Herrera. | 2017 |
| rnpbst: An R package covering non-parametric and bayesian statistical tests | J Carrasco, S García, M del Mar Rueda, F Herrera. | 2017 |
| Cost-Sensitive back-propagation neural networks with binarization techniques in addressing multi-class problems and non-competent classifiers | ZL Zhang, XG Luo, S García, F Herrera. | 2017 |
| A Pareto Based Ensemble with Feature and Instance Selection for Learning from Multi-Class Imbalanced Datasets | A Fernández, CJ Carmona, MJ Jesus, F Herrera. | 2017 |
| An Evolutionary Multi-Objective Model and Instance Selection for Support Vector Machines with Pareto-based Ensembles | A Rosales-Perez, S Garcia, JA Gonzalez, CAC Coello, F Herrera. | 2017 |
| Chi-Spark-RS: An Spark-built evolutionary fuzzy rule selection algorithm in imbalanced classification for big data problems | A Fernandez, E Almansa, F Herrera. | 2017 |
| A first attempt on global evolutionary undersampling for imbalanced big data | I Triguero, M Galar, H Bustince, F Herrera. | 2017 |
| Volume, variety and velocity in Data Science | A Alonso-Betanzos, JA Gámez, F Herrera, JM Puerta, JC Riquelme. | 2017 |
| Neutrality in the sentiment analysis problem based on fuzzy majority | A Valdivia, MV Luzón, F Herrera. | 2017 |
| A Review of Distributed Data Models for Learning | MÁ Rodríguez, A Fernández, A Peregrín, F Herrera. | 2017 |
| Genetic and Memetic Algorithm with Diversity Equilibrium based on Greedy Diversification | A Herrera-Poyatos, F Herrera. | 2017 |
| Big Data Supervised Pairwise Ortholog Detection in Yeasts | DG Cañizares, S del Río García, F Herrera, EA Gallardo, A Antunes, .... | 2017 |
| MapReduce distributed highly random fuzzy forest for noisy big data | F Mustafic, F Herera, N Xiong, SR Gallego. | 2017 |
| Guest Editorial Special Section on Fuzzy Systems in Data Science | J Lu, F Herrera, G Zhang. | 2017 |
| Guest Editorial: Recent Trends in Intelligent Systems | JA Gámez, F Herrera, JM Puerta. | 2017 |
| Conference Report on 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2017)[Conference Reports] | G Acampora, B Siciliano, H Hagras, F Herrera. | 2017 |
| Introducción a los algoritmos metaheurísticos | F Herrera. | 2017 |
| A survey on data preprocessing for data stream mining | S Ramrez-Gallego, B Krawczyk, S Garca, M Woniak, F Herrera. | 2017 |
| Ríos subterráneos y acuíferos kársticos de Venezuela: inventario, situación y conservación | C Galán, F Herrera. | 2017 |
| A view on fuzzy systems for big data: progress and opportunities | A Fernández, CJ Carmona, MJ del Jesus, F Herrera. | 2016 |
| R ultimate multilabel dataset repository | F Charte, D Charte, A Rivera, MJ del Jesus, F Herrera. | 2016 |
| On the impact of dataset complexity and sampling strategy in multilabel classifiers performance | F Charte, A Rivera, MJ del Jesus, F Herrera. | 2016 |
| Ensemble-based classifiers | F Herrera, F Charte, AJ Rivera, MJ del Jesus. | 2016 |
| A position and perspective analysis of hesitant fuzzy sets on information fusion in decision making. Towards high quality progress | RM Rodríguez, B Bedregal, H Bustince, YC Dong, B Farhadinia, .... | 2016 |
| Tutorial on practical tips of the most influential data preprocessing algorithms in data mining | S García, J Luengo, F Herrera. | 2016 |
| Big data preprocessing: methods and prospects | S García, S Ramírez-Gallego, J Luengo, JM Benítez, F Herrera. | 2016 |
| INFFC: an iterative class noise filter based on the fusion of classifiers with noise sensitivity control | JA Sáez, M Galar, J Luengo, F Herrera. | 2016 |
| Evaluating the classifier behavior with noisy data considering performance and robustness: The equalized loss of accuracy measure | JA Sáez, J Luengo, F Herrera. | 2016 |
| From big data to smart data with the k-nearest neighbours algorithm | I Triguero, J Maillo, J Luengo, S García, F Herrera. | 2016 |
| A first study on the use of boosting for class noise reparation | PM Álvarez, J Luengo, F Herrera. | 2016 |
| Comparison of KEEL versus open source Data Mining tools: Knime and Weka software | I Triguero, S González, JM Moyano, S García, J Alcala-Fdez, J Luengo, .... | 2016 |
| A review of hesitant fuzzy sets: Quantitative and qualitative extensions | RM Rodríguez, L Martínez, F Herrera, V Torra. | 2016 |
| NICGAR: a Niching Genetic Algorithm to Mine a Diverse Set of Interesting Quantitative Association Rules | D Martín, J Alcalá-Fdez, A Rosete, F Herrera. | 2016 |
| An optimization-based approach to estimate the range of consistency in hesitant fuzzy linguistic preference relations | CC Li, Y Dong, F Herrera, L Martínez. | 2016 |
| Data discretization: taxonomy and big data challenge | S Ramírez‐Gallego, S García, H Mouriño‐Talín, D Martínez‐Rego, .... | 2016 |
| CONSISTENCY OF HESITANT FUZZY PREFERENCE RELATIONS | RM RODRÍGUEZ, F HERRERA, Y XU, L MARTÍNEZ. | 2016 |
| GPU-SME-kNN: Scalable and memory efficient kNN and lazy learning using GPUs | PD Gutiérrez, M Lastra, J Bacardit, JM Benítez, F Herrera. | 2016 |
| DPD-DFF: A dual phase distributed scheme with double fingerprint fusion for fast and accurate identification in large databases | D Peralta, I Triguero, S García, F Herrera, JM Benitez. | 2016 |
| A forecasting methodology for workload forecasting in cloud systems | FJ Baldán, S Ramírez-Gallego, C Bergmeir, F Herrera, JM Benítez. | 2016 |
| A Wrapper Evolutionary Approach for Supervised Multivariate Discretization: A Case Study on Decision Trees | S Ramírez-Gallego, S García, JM Benítez, F Herrera. | 2016 |
| Ordering-Based Pruning for Improving the Performance of Ensembles of Classifiers in the Framework of Imbalanced Datasets | M Galar, A Fernandez, E Barrenechea, H Bustince, H Francisco. | 2016 |
| Enhancing Evolutionary Fuzzy Systems for Multi-Class Problems: Distance-based Relative Competence Weighting with Truncated Confidences (DRCW-TC) | A Fernandez, M Elkano, M Galar, JA Sanz, S Alshomrani, H Bustince, .... | 2016 |
| A coral reefs optimization algorithm with substrate layers and local search for large scale global optimization | S Salcedo-Sanz, C Camacho-Gómez, D Molina, F Herrera. | 2016 |
| Region-based memetic algorithm with archive for multimodal optimisation | B Lacroix, D Molina, F Herrera. | 2016 |
| Fuzzy-Citation-KNN: a fuzzy nearest neighbor approach for multi-instance classification | P Villar, R Montes, AM Sánchez, F Herrera. | 2016 |
| Una aproximación difusa del vecino más cercano para clasificación multi-instancia | P Villar, R Montes, AM Sanchez, F Herrera. | 2016 |
| Aplicación del uso de valoraciones hesitant lingüísticas en una red social de economía colaborativa | R Montes, AM Sanchez, P Villar, F Herrera. | 2016 |
| A historical account of types of fuzzy sets and their relationships | H Bustince, E Barrenechea, M Pagola, J Fernandez, Z Xu, B Bedregal, .... | 2016 |
| Connecting the linguistic hierarchy and the numerical scale for the 2-tuple linguistic model and its use to deal with hesitant unbalanced linguistic information | Y Dong, CC Li, F Herrera. | 2016 |
| Deriving the priority weights from incomplete hesitant fuzzy preference relations in group decision making | Y Xu, L Chen, RM Rodríguez, F Herrera, H Wang. | 2016 |
| Multilabel Classification: Problem Analysis, Metrics and Techniques | F Herrera, F Charte, AJ Rivera, MJ del Jesus. | 2016 |
| Evolutionary Undersampling Boosting for Imbalanced Classification of Breast Cancer Malignancy | B Krawczyk, M Galar, Ł Jeleń, F Herrera. | 2016 |
| Empowering one-vs-one decomposition with ensemble learning for multi-class imbalanced data | Z Zhang, B Krawczyk, S Garcìa, A Rosales-Pérez, F Herrera. | 2016 |
| Evolutionary fuzzy k-nearest neighbors algorithm using interval-valued fuzzy sets | J Derrac, F Chiclana, S García, F Herrera. | 2016 |
| Evolutionary wrapper approaches for training set selection as preprocessing mechanism for support vector machines: Experimental evaluation and support vector analysis | N Verbiest, J Derrac, C Cornelis, S García, F Herrera. | 2016 |
| Multiple Instance Learning: Foundations and Algorithms | F Herrera, S Ventura, R Bello, C Cornelis, A Zafra, D Sánchez-Tarragó, .... | 2016 |
| A distance-based framework to deal with ordinal and additive inconsistencies for fuzzy reciprocal preference relations | Y Xu, F Herrera, H Wang. | 2016 |
| Managing monotonicity in classification by a pruned adaboost | S González, F Herrera, S García. | 2016 |
| Evolutionary undersampling for extremely imbalanced big data classification under apache spark | I Triguero, M Galar, D Merino, J Maillo, H Bustince, F Herrera. | 2016 |
| Fuzzy Rough Classifiers for Class Imbalanced Multi-instance Data | S Vluymans, DS Tarragó, Y Saeys, C Cornelis, F Herrera. | 2016 |
| Fuzzy-rough imbalanced learning for the diagnosis of High Voltage Circuit Breaker maintenance: The SMOTE-FRST-2T algorithm | E Ramentol, I Gondres, S Lajes, R Bello, Y Caballero, C Cornelis, .... | 2016 |
| Comments on “Interval type-2 fuzzy sets are generalization of interval-valued fuzzy sets: towards a wide view on their relationship”[2] | J Mendel, H Hagras, H Bustince Sola, F Herrera. | 2016 |
| On the combination of pairwise and granularity learning for improving fuzzy rule-based classification systems: GL-FARCHD-OVO | P Villar, A Fernández, F Herrera. | 2016 |
| Fuzzy Multi-Instance Classifiers | S Vluymans, D Sanchez Tarrago, Y Saeys, C Cornelis, F Herrera. | 2016 |
| A first approach in evolutionary fuzzy systems based on the lateral tuning of the linguistic labels for big data classification | A Fernández, S del Río, F Herrera. | 2016 |
| Designing optimal harmonic filters in power systems using greedy adaptive Differential Evolution | M Leon, Y Zenlander, N Xiong, F Herrera. | 2016 |
| Trust management for multimedia big data | Z Yan, J Liu, RH Deng, F Herrera. | 2016 |
| New Ordering-Based Pruning Metrics for Ensembles of Classifiers in Imbalanced Datasets | M Galar, A Fernández, E Barrenechea, H Bustince, F Herrera. | 2016 |
| Big Data: Preprocesamiento y calidad de datos | F Herrera. | 2016 |
| DESIGNING FUZZY SYSTEMS FOR BIG DATA: CHALLENGES AND OPPORTUNITIES | F HERRERA. | 2016 |
| Multiple Instance Multiple Label Learning | F Herrera, S Ventura, R Bello, C Cornelis, A Zafra, D Sánchez-Tarragó, .... | 2016 |
| Multi-instance regression | F Herrera, S Ventura, R Bello, C Cornelis, A Zafra, D Sánchez-Tarragó, .... | 2016 |
| Data Reduction | F Herrera, S Ventura, R Bello, C Cornelis, A Zafra, D Sánchez-Tarragó, .... | 2016 |
| Instance-Based Classification Methods | F Herrera, S Ventura, R Bello, C Cornelis, A Zafra, D Sánchez-Tarragó, .... | 2016 |
| Unsupervised Multiple Instance Learning | F Herrera, S Ventura, R Bello, C Cornelis, A Zafra, D Sánchez-Tarragó, .... | 2016 |
| Intercambio de Clases de acuerdo a la Distancia al Enemigo más Cercano para Problemas con Clases altamente No Balanceadas | S González, M Lázaro, AR Figueiras-Vidal, S Garcıa, F Herrera. | 2016 |
| Un Estudio sobre el Preprocesamiento para Redes Neuronales Profundas y Aplicación sobre Reconocimiento de Dıgitos Manuscritos | D Peralta, A Herrera-Poyatos, F Herrera. | 2016 |
| Mapping and measuring lava volumes from 2002 to 2009 at El Reventador Volcano, Ecuador, from field measurements and satellite remote sensing | MF Naranjo, SK Ebmeier, S Vallejo, P Ramón, P Mothes, J Biggs, .... | 2016 |
| Comparación entre la citología por aspiración con aguja fina y la biopsia por congelación en el diagnóstico de las neoplasias malignas de la glándula tiroides:: un estudio … | C Osorio, A Fernández, C Ensuncho, K Redondo, F Herrera. | 2016 |
| Sensibilidad y especificidad de la citología obtenida mediante aspiración con aguja fina en el diagnóstico de las neoplasias foliculares de la glándula tiroides: un estudio … | C Osorio, A Fernández, K Herrera, Á Marrugo, C Ensuncho, K Redondo, .... | 2016 |
| Obstrucción intestinal parcial producida por mucocele apendicular con fistula a íleon proximal | C Ensuncho, C Osorio, Á Marrugo, F Herrera. | 2016 |
| Importancia de las dinámicas territoriales en la construcción social de mercados y la seguridad alimentaria y nutricional | Y Aranda-Camacho, A Parrado, CA Ramírez, MC Hernández, F Herrera, .... | 2016 |
| Addressing imbalance in multilabel classification: Measures and random resampling algorithms | F Charte, AJ Rivera, MJ del Jesus, F Herrera. | 2015 |
| MLSMOTE: Approaching imbalanced multilabel learning through synthetic instance generation | F Charte, AJ Rivera, MJ del Jesus, F Herrera. | 2015 |
| QUINTA: a question tagging assistant to improve the answering ratio in electronic forums | F Charte, AJ Rivera, MJ del Jesus, F Herrera. | 2015 |
| Resampling multilabel datasets by decoupling highly imbalanced labels | F Charte, A Rivera, MJ del Jesus, F Herrera. | 2015 |
| Revisiting evolutionary fuzzy systems: Taxonomy, applications, new trends and challenges | A Fernandez, V Lopez, MJ del Jesus, F Herrera. | 2015 |
| Addressing overlapping in classification with imbalanced datasets: A first multi-objective approach for feature and instance selection | A Fernández, MJ del Jesus, F Herrera. | 2015 |
| SMOTE–IPF: Addressing the noisy and borderline examples problem in imbalanced classification by a re-sampling method with filtering | JA Sáez, J Luengo, J Stefanowski, F Herrera. | 2015 |
| Using the One-vs-One decomposition to improve the performance of class noise filters via an aggregation strategy in multi-class classification problems | LPF Garcia, JA Sáez, J Luengo, AC Lorena, AC de Carvalho, F Herrera. | 2015 |
| An automatic extraction method of the domains of competence for learning classifiers using data complexity measures | J Luengo, F Herrera. | 2015 |
| Computing with words for decision making versus linguistic decision making: a reflection on both scenarios | F Herrera, E Herrera-Viedma, L Martínez. | 2015 |
| A linguistic 2-tuple multicriteria decision making model dealing with hesitant linguistic information | RM Rodríguez, L Martínez, F Herrera. | 2015 |
| MOPNAR-BigData: un diseno MapReduce para la extracción de reglas de asociación cuantitativas en problemas de Big Data | D Martín, M Martínez-Ballesteros, S Río, J Alcalá-Fdez, J Riquelme, .... | 2015 |
| HYBRID COMPUTATIONAL INTELLIGENCE | A Fernández, R Alcalá, JM Benítez, F Herrera. | 2015 |
| Linguistic Decision Making and Computing with Words | L Martínez, RM Rodriguez, F Herrera. | 2015 |
| Cost-sensitive linguistic fuzzy rule based classification systems under the MapReduce framework for imbalanced big data | V López, S Del Río, JM Benítez, F Herrera. | 2015 |
| frbs: Fuzzy rule-based systems for classification and regression in R | LS Riza, CN Bergmeir, F Herrera, JM Benítez Sánchez. | 2015 |
| A survey on fingerprint minutiae-based local matching for verification and identification: Taxonomy and experimental evaluation | D Peralta, M Galar, I Triguero, D Paternain, S García, E Barrenechea, .... | 2015 |
| ROSEFW-RF: the winner algorithm for the ECBDL’14 big data competition: an extremely imbalanced big data bioinformatics problem | I Triguero, S del Río, V López, J Bacardit, JM Benítez, F Herrera. | 2015 |
| A mapreduce approach to address big data classification problems based on the fusion of linguistic fuzzy rules | S del Rio, V Lopez, JM Benítez, F Herrera. | 2015 |
| Evolutionary feature selection for big data classification: A mapreduce approach | D Peralta, S del Río, S Ramírez-Gallego, I Triguero, JM Benitez, F Herrera. | 2015 |
| A survey of fingerprint classification Part I: Taxonomies on feature extraction methods and learning models | M Galar, J Derrac, D Peralta, I Triguero, D Paternain, C Lopez-Molina, .... | 2015 |
| A survey of fingerprint classification Part II: Experimental analysis and ensemble proposal | M Galar, J Derrac, D Peralta, I Triguero, D Paternain, C Lopez-Molina, .... | 2015 |
| Multivariate discretization based on evolutionary cut points selection for classification | S Ramírez-Gallego, S García, JM Benítez, F Herrera. | 2015 |
| Fast fingerprint identification using GPUs | M Lastra, J Carabaño, PD Gutiérrez, JM Benítez, F Herrera. | 2015 |
| Distributed entropy minimization discretizer for big data analysis under apache spark | S Ramírez-Gallego, S García, H Mouriño-Talín, D Martínez-Rego, .... | 2015 |
| Analysis of data preprocessing increasing the oversampling ratio for extremely imbalanced big data classification | S del Río, JM Benítez, F Herrera. | 2015 |
| Package ‘RoughSets’ | LS Riza, A Janusz, D Slezak, C Cornelis, F Herrera, JM Benitez, .... | 2015 |
| On the combination of genetic fuzzy systems and pairwise learning for improving detection rates on intrusion detection systems | S Elhag, A Fernández, A Bawakid, S Alshomrani, F Herrera. | 2015 |
| DRCW-OVO: distance-based relative competence weighting combination for one-vs-one strategy in multi-class problems | M Galar, A Fernández, E Barrenechea, F Herrera. | 2015 |
| A proposal for evolutionary fuzzy systems using feature weighting: dealing with overlapping in imbalanced datasets | S Alshomrani, A Bawakid, SO Shim, A Fernández, F Herrera. | 2015 |
| On the impact of Distance-based Relative Competence Weighting approach in One-vs-One classification for Evolutionary Fuzzy Systems: DRCW-FH-GBML algorithm | A Fernández, M Galar, JA Sanz, H Bustince, O Cordón, F Herrera. | 2015 |
| A walk into metaheuristics for engineering optimization: principles, methods and recent trends | N Xiong, D Molina, ML Ortiz, F Herrera. | 2015 |
| Iterative hybridization of DE with local search for the CEC'2015 special session on large scale global optimization | D Molina, F Herrera. | 2015 |
| A web tool to support decision making in the housing market using hesitant fuzzy linguistic term sets | R Montes, AM Sánchez, P Villar, F Herrera. | 2015 |
| Hibridación iterativa de DE con búsqueda local con reinicio para problemas de alta dimensionalidad | D Molina, F Herrera. | 2015 |
| Improving the OVO performance in fuzzy rule-based classification systems by the genetic learning of the granularity level | P Villar, A Fernández, R Montes, AM Sánchez, F Herreraz. | 2015 |
| Self-labeled techniques for semi-supervised learning: taxonomy, software and empirical study | I Triguero, S García, F Herrera. | 2015 |
| MRPR: A MapReduce solution for prototype reduction in big data classification | I Triguero, D Peralta, J Bacardit, S García, F Herrera. | 2015 |
| Minimizing adjusted simple terms in the consensus reaching process with hesitant linguistic assessments in group decision making | Y Dong, X Chen, F Herrera. | 2015 |
| Interval Type-2 Fuzzy Sets are generalization of Interval-Valued Fuzzy Sets: Towards a Wider view on their relationship | H Bustince Sola, J Fernandez, H Hagras, F Herrera, M Pagola, .... | 2015 |
| A Compact Evolutionary Interval-Valued Fuzzy Rule-Based Classification System for the Modeling and Prediction of Real-World Financial Applications with Imbalanced Data | J Sanz, D Bernardo, F Herrera, H Bustince Sola, H Hagras. | 2015 |
| Máster en Ciencia de Datos e Ingeniería de Computadores: una apuesta por la formación especializada en el sector de las TIC | F Rojas Ruiz, A Cano Utrera, M Gómez Olmedo, J Ortega Lopera, .... | 2015 |
| The 2-tuple Linguistic Model: Computing with Words in Decision Making | L Martínez, RM Rodriguez, F Herrera. | 2015 |
| Enhancing multi-class classification in FARC-HD fuzzy classifier: On the synergy between n-dimensional overlap functions and decomposition strategies | M Elkano, M Galar, J Sanz, A Fernandez, E Barrenechea, F Herrera, .... | 2015 |
| An optimization-based approach to adjusting unbalanced linguistic preference relations to obtain a required consistency level | Y Dong, CC Li, F Herrera. | 2015 |
| SEG-SSC: A Framework Based on Synthetic Examples Generation for Self-Labeled Semi-Supervised Classification | I Triguero, S García, F Herrera. | 2015 |
| A mapreduce-based k-nearest neighbor approach for big data classification | J Maillo, I Triguero, F Herrera. | 2015 |
| Monotonic random forest with an ensemble pruning mechanism based on the degree of monotonicity | S González, F Herrera, S García. | 2015 |
| IFROWANN: Imbalanced Fuzzy-Rough Ordered Weighted Average Nearest Neighbor Classification | E Ramentol, S Vluymans, N Verbiest, Y Caballero, R Bello Perez, .... | 2015 |
| On the Usefulness of One-Class Classifier Ensembles for Decomposition of Multi-Class Problems | B Krawczyk, M Woźniak, F Herrera. | 2015 |
| Javanpst: Nonparametric statistical tests in java | J Derrac, S García, F Herrera. | 2015 |
| Managing monotonicity in classification by a pruned random forest | S González, F Herrera, S García. | 2015 |
| An interval valued k-nearest neighbors classifier | J Derrac, F Chiclana, S Garcia, F Herrera. | 2015 |
| Evolutionary undersampling for imbalanced big data classification | I Triguero, M Galar, S Vluymans, C Cornelis, H Bustince, F Herrera, .... | 2015 |
| An Effective Big Data Supervised Imbalanced Classification Approach for Ortholog Detection in Related Yeast Species | D Galpert, S del Río, F Herrera, E Ancede-Gallardo, A Antunes, .... | 2015 |
| A tour on big data classification: Selected Computational Intelligence approaches | F Herrera. | 2015 |
| Máster en Ciencia de Datos e Ingeniería de Computadores: una apuesta por la formación especializada en el sector TIC | F Rojas, A Cano, M Gómez, J Ortega, F Herrera, R Romero-Zaliz, .... | 2015 |
| Classification of binary imbalanced data using a bayesian ensemble of bayesian neural networks | M Lázaro, F Herrera, AR Figueiras-Vidal. | 2015 |
| Improving Pairwise Learning Classification in Fuzzy Rule Based Classification Systems Using Dynamic Classifier Selection | A Fernández, M Galar, JA Sanz, H Bustince, F Herrera. | 2015 |
| Clasificación Monotónica mediante poda de Bosques Aleatorios | S González, F Herrera, S Garcıa. | 2015 |
| Un enfoque MapReduce del algoritmo k-vecinos más cercanos para Big Data | J Maillo, I Triguero, F Herrera. | 2015 |
| Pairwise Ortholog Detection in Related Yeast Species by Using Big Data Supervised Classifications | DG Cañizares, S del Río García, F Herrera, EA Gallardo, A Antunes, .... | 2015 |
| Feature selection | S García, J Luengo, F Herrera, S García, J Luengo, F Herrera. | 2015 |
| Utilidad de la citología obtenida mediante aspiración con aguja fina en el diagnóstico de las neoplasias foliculares de la glándula tiroides en la ESE Hospital Universitario … | F Herrera, K Redondo, C Osorio, J Grice, A Fernández. | 2015 |
| Dealing with missing values | S García, J Luengo, F Herrera, S García, J Luengo, F Herrera. | 2015 |
| Dealing with noisy data | S García, J Luengo, F Herrera, S García, J Luengo, F Herrera. | 2015 |
| Instance selection | S García, J Luengo, F Herrera, S García, J Luengo, F Herrera. | 2015 |
| Data preparation basic models | S García, J Luengo, F Herrera, S García, J Luengo, F Herrera. | 2015 |
| Discretization | S García, J Luengo, F Herrera, S García, J Luengo, F Herrera. | 2015 |
| Data Sets and Proper Statistical Analysis of Data Mining Techniques | S García, J Luengo, F Herrera, S García, J Luengo, F Herrera. | 2015 |
| A data mining software package including data preparation and reduction: keel | S García, J Luengo, F Herrera, S García, J Luengo, F Herrera. | 2015 |
| Data Preprocessing | F Herrera. | 2015 |
| Addressing imbalanced classification with instance generation techniques: IPADE-ID | V López, I Triguero, CJ Carmona, S García, F Herrera. | 2014 |
| Overview on evolutionary subgroup discovery: analysis of the suitability and potential of the search performed by evolutionary algorithms | CJ Carmona, P González, MJ del Jesus, F Herrera. | 2014 |
| METSK-HDe: A multiobjective evolutionary algorithm to learn accurate TSK-fuzzy systems in high-dimensional and large-scale regression problems | MJ Gacto, M Galende, R Alcalá, F Herrera. | 2014 |
| Concurrence among imbalanced labels and its influence on multilabel resampling algorithms | F Charte, A Rivera, MJ del Jesus, F Herrera. | 2014 |
| LI-MLC: A Label Inference Methodology for Addressing High Dimensionality in the Label Space for Multilabel Classification | F Charte, AJ Rivera, MJ Del Jesus, F Herrera. | 2014 |
| FLINTSTONES: A fuzzy linguistic decision tools enhancement suite based on the 2-tuple linguistic model and extensions | FJ Estrella, M Espinilla, F Herrera, L Martínez. | 2014 |
| MLeNN: a first approach to heuristic multilabel undersampling | F Charte, AJ Rivera, MJ del Jesus, F Herrera. | 2014 |
| Big Data with Cloud Computing: an insight on the computing environment, MapReduce, and programming frameworks | A Fernández, S del Río, V López, A Bawakid, MJ del Jesus, JM Benítez, .... | 2014 |
| Hesitant fuzzy sets: state of the art and future directions | RM Rodríguez, L Martínez, V Torra, ZS Xu, F Herrera. | 2014 |
| Consensus under a fuzzy context: Taxonomy, analysis framework AFRYCA and experimental case of study | I Palomares, FJ Estrella, L Martínez, F Herrera. | 2014 |
| MENTOR: A graphical monitoring tool of preferences evolution in large-scale group decision making | I Palomares, L Martínez, F Herrera. | 2014 |
| Data Preprocessing in Data Mining | S García, J Luengo, F Herrera. | 2014 |
| Analyzing the presence of noise in multi-class problems: alleviating its influence with the one-vs-one decomposition | JA Sáez, M Galar, J Luengo, F Herrera. | 2014 |
| On the characterization of noise filters for self-training semi-supervised in nearest neighbor classification | I Triguero, JA Sáez, J Luengo, S García, F Herrera. | 2014 |
| Statistical computation of feature weighting schemes through data estimation for nearest neighbor classifiers | JA Sáez, J Derrac, J Luengo, F Herrera. | 2014 |
| Managing borderline and noisy examples in imbalanced classification by combining SMOTE with ensemble filtering | JA Sáez, J Luengo, J Stefanowski, F Herrera. | 2014 |
| Hesitant Fuzzy Sets: An Emerging Tool in Decision Making. | F Herrera, L Martínez-López, V Torra, Z Xu. | 2014 |
| Improving the behavior of the nearest neighbor classifier against noisy data with feature weighting schemes | JA Sáez, J Derrac, J Luengo, F Herrera. | 2014 |
| QAR-CIP-NSGA-II: A new multi-objective evolutionary algorithm to mine quantitative association rules | D Martín, A Rosete, J Alcalá-Fdez, F Herrera. | 2014 |
| A multi-objective evolutionary method for learning granularities based on fuzzy discretization to improve the accuracy-complexity trade-off of fuzzy rule-based classification … | M Fazzolari, R Alcalá, F Herrera. | 2014 |
| A review of microarray datasets and applied feature selection methods | V Bolón-Canedo, N Sánchez-Marono, A Alonso-Betanzos, JM Benítez, .... | 2014 |
| On the use of MapReduce for imbalanced big data using Random Forest | S Del Río, V López, JM Benítez, F Herrera. | 2014 |
| Implementing algorithms of rough set theory and fuzzy rough set theory in the R package “roughsets” | LS Riza, A Janusz, C Bergmeir, C Cornelis, F Herrera, D Śle, JM Benítez. | 2014 |
| Fast fingerprint identification for large databases | D Peralta, I Triguero, R Sanchez-Reillo, F Herrera, JM Benítez. | 2014 |
| E-learning and educational data mining in cloud computing: an overview | A Fernández, D Peralta, JM Benítez, F Herrera. | 2014 |
| Minutiae filtering to improve both efficacy and efficiency of fingerprint matching algorithms | D Peralta, M Galar, I Triguero, O Miguel-Hurtado, JM Benitez, F Herrera. | 2014 |
| Learning from data using the R package" FRBS" | LS Riza, C Bergmeir, F Herrera, JM Benitez. | 2014 |
| On the use of MapReduce to build linguistic fuzzy rule based classification systems for big data | V López, S del Rio, JM Benitez, F Herrera. | 2014 |
| Package ‘frbs’ | LS Riza, C Bergmeir, F Herrera, JM Benitez. | 2014 |
| Constructing fuzzy rule-based systems with the R package “frbs” | LS Riza, C Bergmeir, F Herrera, JM Benítez. | 2014 |
| On the importance of the validation technique for classification with imbalanced datasets: Addressing covariate shift when data is skewed | V López, A Fernández, F Herrera. | 2014 |
| Empowering difficult classes with a similarity-based aggregation in multi-class classification problems | M Galar, A Fernández, E Barrenechea, F Herrera. | 2014 |
| Enhancing difficult classes in one-vs-one classifier fusion strategy using restricted equivalence functions | M Galar, E Barrenechea, A Fernández, F Herrera. | 2014 |
| Region based memetic algorithm for real-parameter optimisation | B Lacroix, D Molina, F Herrera. | 2014 |
| Influence of regions on the memetic algorithm for the cec'2014 special session on real-parameter single objective optimisation | D Molina, B Lacroix, F Herrera. | 2014 |
| Designing a compact genetic fuzzy rule-based system for one-class classification | P Villar, B Krawczyk, AM Sánchez, R Montes, F Herrera. | 2014 |
| A Consensus Model to Detect and Manage Non-Cooperative Behaviors in Large Scale Group Decision Making | I Palomares, L Martınez, F Herrera. | 2014 |
| Fuzzy nearest neighbor algorithms: Taxonomy, experimental analysis and prospects | J Derrac, S García, F Herrera. | 2014 |
| A New Multi-Objective Evolutionary Algorithm for Mining a Reduced Set of Interesting Positive and Negative Quantitative Association Rules | D Martin, A Rosete, J Alcalá-Fdez, F Herrera. | 2014 |
| Analyzing convergence performance of evolutionary algorithms: a statistical approach | J Derrac, S García, S Hui, PN Suganthan, F Herrera. | 2014 |
| Metsk-hd e: A multiobjective evolutionary algorithm to learn accurate tsk-fuzzy systems in high-dimensional and large-scale regression problems | MJ Gacto, M Galende, R Alcalá, F Herrera. | 2014 |
| Preprocessing noisy imbalanced datasets using SMOTE enhanced with fuzzy rough prototype selection | N Verbiest, E Ramentol, C Cornelis, F Herrera. | 2014 |
| A combined mapreduce-windowing two-level parallel scheme for evolutionary prototype generation | I Triguero, D Peralta, J Bacardit, S García, F Herrera. | 2014 |
| A first attempt on evolutionary prototype reduction for nearest neighbor one-class classification | B Krawczyk, I Triguero, S García, M Woźniak, F Herrera. | 2014 |
| On the statistical analysis of the parameters’ trend in a machine learning algorithm | S García, J Derrac, S Ramírez-Gallego, F Herrera. | 2014 |
| An insight into the importance of national university rankings in an international context: the case of the I-UGR rankings of Spanish universities | N Robinson-García, D Torres-Salinas, ED López-Cózar, F Herrera. | 2014 |
| A multi-instance learning wrapper based on the Rocchio classifier for web index recommendation | DS Tarragó, C Cornelis, R Bello, F Herrera. | 2014 |
| Weighted one-class classification for different types of minority class examples in imbalanced data | B Krawczyk, M Woźniak, F Herrera. | 2014 |
| Connecting the numerical scale model to the unbalanced linguistic term sets | Y Dong, CC Li, F Herrera. | 2014 |
| A preliminary study on fingerprint classification using fuzzy rule-based classification systems | M Galar, J Sanz, M Pagola, H Bustince, F Herrera. | 2014 |
| Challenges of computing with words in decision making | L Martínez, F Herrera. | 2014 |
| Big data: Procesando los datos en la sociedad digital | F Herrera. | 2014 |
| Improving the Performance of FARC-HD in Multi-class Classification Problems Using the One-Versus-One Strategy and an Adaptation of the Inference System | M Elkano, M Galar, J Sanz, E Barrenechea, F Herrera, H Bustince. | 2014 |
| Information Fusion: Greetings from the new Editor-in-Chief | F Herrera. | 2014 |
| Rendimiento diagnóstico de la citología por aspiración con aguja fina en pacientes con nódulo tiroideo en la ESE Hospital Universitario del Caribe | F Herrera, S Castañeda, S Contreras, A Fernández, E Pérez. | 2014 |
| Obtaining accurate TSK fuzzy rule-based systems by multi-objective evolutionary learning in high-dimensional regression problems | MJ Gacto, M Galende, R Alcalá, F Herrera. | 2013 |
| A first approach to deal with imbalance in multi-label datasets | F Charte, A Rivera, MJ del Jesus, F Herrera. | 2013 |
| Analysing the classification of imbalanced data-sets with multiple classes: Binarization techniques and ad-hoc approaches | A FernáNdez, V LóPez, M Galar, MAJ Del Jesus, F Herrera. | 2013 |
| A hierarchical genetic fuzzy system based on genetic programming for addressing classification with highly imbalanced and borderline data-sets | V LóPez, A FernáNdez, MAJ Del Jesus, F Herrera. | 2013 |
| Predicting noise filtering efficacy with data complexity measures for nearest neighbor classification | JA SáEz, JN Luengo, F Herrera. | 2013 |
| Tackling the problem of classification with noisy data using Multiple Classifier Systems: Analysis of the performance and robustness | JA SáEz, M Galar, JN Luengo, F Herrera. | 2013 |
| An Experimental Case of Study on the Behavior of Multiple Classifier Systems with Class Noise Datasets | JA Sáez, M Galar, J Luengo, F Herrera. | 2013 |
| Eliciting comparative linguistic expressions in group decision making | RM Rodríguez, L Martínez, F Herrera. | 2013 |
| A study on the application of instance selection techniques in genetic fuzzy rule-based classification systems: Accuracy-complexity trade-off | M Fazzolari, B Giglio, R Alcalá, F Marcelloni, F Herrera. | 2013 |
| Improving a fuzzy association rule-based classification model by granularity learning based on heuristic measures over multiple granularities | M Fazzolari, R Alcala, Y Nojima, H Ishibuchi, F Herrera. | 2013 |
| A high performance fingerprint matching system for large databases based on GPU | PD Gutierrez, M Lastra, F Herrera, JM Benitez. | 2013 |
| Fuzzy Clustering Approach for Non-cooperative Behavior Detection in Consensus Reaching Processes | I Palomares, L Martínez, F Herrera. | 2013 |
| An overview on the structure and applications for business intelligence and data mining in cloud computing | A Fernández, S del Río, F Herrera, JM Benítez. | 2013 |
| An insight into classification with imbalanced data: Empirical results and current trends on using data intrinsic characteristics | V López, A Fernández, S García, V Palade, F Herrera. | 2013 |
| EUSBoost: Enhancing ensembles for highly imbalanced data-sets by evolutionary undersampling | M Galar, A Fernández, E Barrenechea, F Herrera. | 2013 |
| IVTURS: A linguistic fuzzy rule-based classification system based on a new interval-valued fuzzy reasoning method with tuning and rule selection | JA Sanz, A Fernandez, H Bustince, F Herrera. | 2013 |
| Dynamic classifier selection for one-vs-one strategy: avoiding non-competent classifiers | M Galar, A Fernández, E Barrenechea, H Bustince, F Herrera. | 2013 |
| Addressing covariate shift for genetic fuzzy systems classifiers: a case of study with FARC-HD for imbalanced datasets | V López, A Fernández, F Herrera. | 2013 |
| Variable mesh optimization for the 2013 CEC special session niching methods for multimodal optimization | D Molina, A Puris, R Bello, F Herrera. | 2013 |
| Dynamically updated region based memetic algorithm for the 2013 CEC special session and competition on real parameter single objective optimization | B Lacroix, D Molina, F Herrera. | 2013 |
| A group decision making model dealing with comparative linguistic expressions based on hesitant fuzzy linguistic term sets | RM Rodríguez, L Martı́nez, F Herrera. | 2013 |
| A review of the application of multi-objective evolutionary fuzzy systems: Current status and further directions | M Fazzolari, R Alcalá, Y Nojima, H Ishibuchi, F Herrera. | 2013 |
| On the use of evolutionary feature selection for improving fuzzy rough set based prototype selection | J Derrac, N Verbiest, S García, C Cornelis, F Herrera. | 2013 |
| FRPS: A fuzzy rough prototype selection method | N Verbiest, C Cornelis, F Herrera. | 2013 |
| Statistical analysis of convergence performance throughout the evolutionary search: A case study with SaDE-MMTS and Sa-EPSDE-MMTS | J Derrac, S Garcia, S Hui, F Herrera, PN Suganthan. | 2013 |
| On the use of biplot analysis for multivariate bibliometric and scientific indicators | D Torres‐Salinas, N Robinson‐García, E Jiménez‐Contreras, F Herrera, .... | 2013 |
| The role of national university rankings in an international context: The case of the I-UGR Rankings of Spanish Universities | N Robinson-García, JG Moreno-Torres, D Torres-Salinas, .... | 2013 |
| OWA-FRPS: A prototype selection method based on ordered weighted average fuzzy rough set theory | N Verbiest, C Cornelis, F Herrera. | 2013 |
| Our Collaboration with Da | F Herrera, E Herrera-Viedma. | 2013 |
| Special Issue on Evolutionary Fuzzy Systems EFSs | R Alcalá, Y Nojima, H Ishibuchi, F Herrera. | 2013 |
| 7th International Conference on Knowledge Management in Organizations: Service and Cloud Computing | L Uden, F Herrera, JB Pérez, JMC Rodriguez. | 2013 |
| Special Issue on" Evolutionary Fuzzy Systems" EFSs | R Alcalá, Y Nojima, H Ishibuchi, F Herrera. | 2013 |
| Evolutionary-based selection of generalized instances for imbalanced classification | S Garcı, I Triguero, CJ Carmona, F Herrera. | 2012 |
| A Preliminary Study on Selecting the Optimal Cut Points in Discretization by Evolutionary Algorithms. | S García, V López, J Luengo, CJ Carmona, F Herrera. | 2012 |
| A multi-objective evolutionary algorithm for an effective tuning of fuzzy logic controllers in heating, ventilating and air conditioning systems | MJ Gacto, R Alcalá, F Herrera. | 2012 |
| Improving multi-label classifiers via label reduction with association rules | F Charte, A Rivera, MJ del Jesus, F Herrera. | 2012 |
| An overview on the 2-tuple linguistic model for computing with words in decision making: Extensions, applications and challenges | L Martı, F Herrera. | 2012 |
| A survey of discretization techniques: Taxonomy and empirical analysis in supervised learning | S Garcia, J Luengo, JA Sáez, V Lopez, F Herrera. | 2012 |
| On the choice of the best imputation methods for missing values considering three groups of classification methods | J Luengo, S García, F Herrera. | 2012 |
| Missing data imputation for fuzzy rule-based classification systems | J Luengo, JA Sáez, F Herrera. | 2012 |
| Shared domains of competence of approximate learning models using measures of separability of classes | J Luengo, F Herrera. | 2012 |
| A first study on decomposition strategies with data with class noise using decision trees | JA Sáez, M Galar, J Luengo, F Herrera. | 2012 |
| On the suitability of fuzzy rule-based classification systems with noisy data | J Saez, J Luengo, F Herrera. | 2012 |
| Hybrid laser pointer detection algorithm based on template matching and fuzzy rule-based systems for domotic control in real home environments | F Chávez, F Fernández, R Alcalá, J Alcalá-Fdez, G Olague, F Herrera. | 2012 |
| A case study on the application of instance selection techniques for Genetic Fuzzy Rule-Based Classifiers | B Giglio, F Marcelloni, M Fazzolari, R Alcala, F Herrera. | 2012 |
| Group decision making with comparative linguistic terms | RM Rodríguez, L Martínez, F Herrera. | 2012 |
| An overview of e-learning in cloud computing | A Fernandez, D Peralta, F Herrera, JM Benítez. | 2012 |
| Special issue on “new trends in data mining” NTDM | JM Benítez, N García-Pedrajas, F Herrera. | 2012 |
| A review on ensembles for the class imbalance problem: bagging-, boosting-, and hybrid-based approaches | M Galar, A Fernández, E Barrenechea, H Bustince, F Herrera. | 2012 |
| Analysis of preprocessing vs. cost-sensitive learning for imbalanced classification. Open problems on intrinsic data characteristics | V López, A Fernández, JG Moreno-Torres, F Herrera. | 2012 |
| Feature selection and granularity learning in genetic fuzzy rule-based classification systems for highly imbalanced data-sets | P Villar, A Fernandez, RA Carrasco, F Herrera. | 2012 |
| IIVFDT: Ignorance functions based interval-valued fuzzy decision tree with genetic tuning | J Sanz, H Bustince, A Fernández, F Herrera. | 2012 |
| Linguistic fuzzy rules in data mining: follow-up Mamdani fuzzy modeling principle | A Fernández, F Herrera. | 2012 |
| SciMAT: A new science mapping analysis software tool | MJ Cobo, AG López‐Herrera, E Herrera‐Viedma, F Herrera. | 2012 |
| A Note on the ITS Topic Evolution in the Period 2000–2009 at T-ITS | MJ Cobo, AG López-Herrera, F Herrera, E Herrera-Viedma. | 2012 |
| Variable mesh optimization for continuous optimization problems | A Puris, R Bello, D Molina, F Herrera. | 2012 |
| Region based memetic algorithm with LS chaining | B Lacroix, D Molina, F Herrera. | 2012 |
| Optimising real parameters using the information of a mesh of solutions: VMO algorithm | A Puris, R Bello, D Molina, F Herrera. | 2012 |
| Modeling dynamics of a real-coded CHC algorithm in terms of dynamical probability distributions | J Marín, D Molina, F Herrera. | 2012 |
| Hesitant Fuzzy Linguistic Terms Sets for Decision Making | R Rodriguez, L Martinez, F Herrera. | 2012 |
| A unifying view on dataset shift in classification | JG Moreno-Torres, T Raeder, R Alaiz-Rodríguez, NV Chawla, F Herrera. | 2012 |
| A taxonomy and experimental study on prototype generation for nearest neighbor classification | I Triguero, J Derrac, S Garcia, F Herrera. | 2012 |
| SMOTE-RSB*: a hybrid preprocessing approach based on oversampling and undersampling for high imbalanced data-sets using SMOTE and rough sets theory | E Ramentol, Y Caballero, R Bello, F Herrera. | 2012 |
| Study on the Impact of Partition-Induced Dataset Shift on -Fold Cross-Validation | JG Moreno-Torres, JA Sáez, F Herrera. | 2012 |
| Grouping, Overlap and Generalized Bi-Entropic Functions for Fuzzy Modeling of Pairwise Comparisons | H Bustince Sola, M Pagola, R Mesiar, E Hullermeier, F Herrera. | 2012 |
| Enhancing Evolutionary Instance Selection Algorithms by means of Fuzzy Rough Set based Feature Selection | J Derrac, C Cornelis, S García, F Herrera. | 2012 |
| Integrating a differential evolution feature weighting scheme into prototype generation | I Triguero, JN Derrac, S GarcíA, F Herrera. | 2012 |
| Integrating Instance Selection, Instance Weighting, and Feature Weighting for Nearest Neighbor Classifiers by Coevolutionary Algorithms. | J Derrac, I Triguero, S García, F Herrera. | 2012 |
| A co-evolutionary framework for nearest neighbor enhancement: Combining instance and feature weighting with instance selection | J Derrac, I Triguero, S García, F Herrera. | 2012 |
| Analysis of new niching genetic algorithms for finding multiple solutions in the job shop scheduling | E Pérez, M Posada, F Herrera. | 2012 |
| Efecto de la agregación de universidades españolas en el Ranking de Shanghai (ARWU): caso de las comunidades autónomas y los campus de excelencia | D Docampo, T Luque-Martínez, D Torres-Salinas, F Herrera. | 2012 |
| SMOTE-FRST: a new resampling method using fuzzy rough set theory | E Ramentol, N Verbiest, R Bello, Y Caballero, C Cornelis, F Herrera. | 2012 |
| Improving SMOTE with fuzzy rough prototype selection to detect noise in imbalanced classification data | N Verbiest, E Ramentol, C Cornelis, F Herrera. | 2012 |
| Ranking of research output of universities on the basis of the multidimensional prestige of influential fields: Spanish universities as a case of study | JA García, R Rodriguez-Sánchez, J Fdez-Valdivia, D Torres-Salinas, .... | 2012 |
| COST SENSITIVE AND PREPROCESSING FOR CLASSIFICATION WITH IMBALANCED DATA-SETS: SIMILAR BEHAVIOUR AND POTENTIAL HYBRIDIZATIONS | V López, A Fernández, MJ del Jesus, F Herrera. | 2012 |
| E-mail: herreraðdecsai. ugr. es | F Herrera, E Herrera-Viedma. | 2012 |
| Aggregate ranking of Spain's universities in the Shanghai Ranking (ARWU): Effect on autonomous communities and campuses of international excellence | D Docampo, F Herrera, T Luque-Martínez, D Torres-Salinas. | 2012 |
| Selección de prototipos basada en conjuntos rugosos difusos | N Verbiest, C Cornelis, F Herrera. | 2012 |
| Algoritmos Basados en Nubes de Partıculas y Evolución Diferencial para el Problema de Optimización Continua: Un estudio experimental | PD Gutiérrez, I Triguero, F Herrera. | 2012 |
| Linguistic Information: Issues and Analysis | F Herrera, E Herrera-Viedma, L Martínez. | 2012 |
| Ranking of Research Output of Spanish Universities on the Basis of the Multidimensional Prestige of Influential Fields of Study | JA García, R Rodríguez-Sánchez, J Fdez-Valdivia, D Torres-Salinas, .... | 2012 |
| Special issue on" New Trends in Data Mining" NTDM | JM Benítez, N García-Pedrajas, F Herrera. | 2012 |
| Rankings de universidades: llegaron para quedarse | F Herrera Triguero, D Torres-Salinas, E Delgado López-Cózar. | 2012 |
| An extension on | S Garcia, F Herrera. | 2012 |
| Identificación Inteligente de un Proceso Fermentativo Usando el Algoritmo GMDH Modificado | F Hernández, F Herrera. | 2012 |
| An overview on subgroup discovery: foundations and applications | F Herrera, CJ Carmona, P González, MJ Del Jesus. | 2011 |
| Evolutionary selection of hyperrectangles in nested generalized exemplar learning | S García, J Derrac, J Luengo, CJ Carmona, F Herrera. | 2011 |
| Analysis of the impact of using different diversity functions for the subgroup discovery algorithm NMEEF-SD | CJ Carmona, P González, MJ del Jesus, F Herrera. | 2011 |
| Interpretability of linguistic fuzzy rule-based systems: An overview of interpretability measures | MJ Gacto, R Alcalá, F Herrera. | 2011 |
| Evolutionary multi-objective algorithm to effectively improve the performance of the classic tuning of fuzzy logic controllers for a heating, ventilating and air conditioning … | MJ Gacto, R Alcalá, F Herrera. | 2011 |
| A double axis classification of interpretability measures for linguistic fuzzy rule-based systems | MJ Gacto, R Alcalá, F Herrera. | 2011 |
| Prototype selection for nearest neighbor classification: Taxonomy and empirical study | S Garcia, J Derrac, JR Cano, F Herrera. | 2011 |
| On the usefulness of fuzzy rule based systems based on hierarchical linguistic fuzzy partitions | A Fernández, V López, MJ Del Jesus, F Herrera. | 2011 |
| Addressing data complexity for imbalanced data sets: analysis of SMOTE-based oversampling and evolutionary undersampling | J Luengo, A Fernández, S García, F Herrera. | 2011 |
| Fuzzy rule based classification systems versus crisp robust learners trained in presence of class noise's effects: a case of study | JA Sáez, J Luengo, F Herrera. | 2011 |
| Imputation of Missing Values | J Luengo, S Garcıa, F Herrera. | 2011 |
| KEEL data-mining software tool: Data set repository, integration of algorithms and experimental analysis framework | J Alcala-Fdez, A Fernández, J Luengo, J Derrac, S García, L Sánchez, .... | 2011 |
| A fuzzy association rule-based classification model for high-dimensional problems with genetic rule selection and lateral tuning | J Alcala-Fdez, R Alcala, F Herrera. | 2011 |
| A multi-objective evolutionary algorithm for mining quantitative association rules | D Martín, A Rosete, J Alcalá-Fdez, F Herrera. | 2011 |
| Evolutionary learning of a laser pointer detection fuzzy system for an environment control system | F Chávez, F Fernández, R Alcalá, J Alcalá-Fdez, F Herrera. | 2011 |
| Multiobjective genetic fuzzy rule selection of single granularity-based fuzzy classification rules and its interaction with the lateral tuning of membership functions | R Alcalá, Y Nojima, F Herrera, H Ishibuchi. | 2011 |
| Musical genre classification by means of fuzzy rule-based systems: A preliminary approach | F Fernández, F Chávez, R Alcalá, F Herrera. | 2011 |
| Special issue on evolutionary fuzzy systems | Y Nojima, R Alcalá, H Ishibuchi, F Herrera. | 2011 |
| Applying linguistic OWA operators in consensus models under unbalanced linguistic information | E Herrera-Viedma, FJ Cabrerizo, IJ Pérez, MJ Cobo, S Alonso, F Herrera. | 2011 |
| A Multicriteria Linguistic Decision Making Model Dealing with Comparative Terms | RM Rodríguez, L Martínez, F Herrera. | 2011 |
| Trends in Applied Intelligent Systems: 23rd International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2010, Cordoba … | N García-Pedrajas, F Herrera, C Fyfe, JMB Sánchez, M Ali. | 2011 |
| An overview of ensemble methods for binary classifiers in multi-class problems: Experimental study on one-vs-one and one-vs-all schemes | M Galar, A Fernández, E Barrenechea, H Bustince, F Herrera. | 2011 |
| A genetic tuning to improve the performance of fuzzy rule-based classification systems with interval-valued fuzzy sets: Degree of ignorance and lateral position | J Sanz, A Fernández, H Bustince, F Herrera. | 2011 |
| Addressing the classification with imbalanced data: open problems and new challenges on class distribution | A Fernández, S García, F Herrera. | 2011 |
| A case study on medical diagnosis of cardiovascular diseases using a genetic algorithm for tuning fuzzy rule-based classification systems with interval-valued fuzzy sets | J Sanz, M Pagola, H Bustince, A Brugos, A Fernández, F Herrera. | 2011 |
| Construction of interval-valued fuzzy preference relations using ignorance functions: Interval-valued non dominance criterion | E Barrenechea, A Fernández, F Herrera, H Bustince. | 2011 |
| Studying the behavior of a multiobjective genetic algorithm to design fuzzy rule-based classification systems for imbalanced data-sets | P Villar, A Fernández, F Herrera. | 2011 |
| On the cooperation of interval-valued fuzzy sets and genetic tuning to improve the performance of fuzzy decision trees | JA Sanz, H Bustince, A Fernández, F Herrera. | 2011 |
| Science mapping software tools: Review, analysis, and cooperative study among tools | MJ Cobo, AG López‐Herrera, E Herrera‐Viedma, F Herrera. | 2011 |
| Memetic algorithms based on local search chains for large scale continuous optimisation problems: MA-SSW-Chains | D Molina, M Lozano, AM Sánchez, F Herrera. | 2011 |
| A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms | J Derrac, S García, D Molina, F Herrera. | 2011 |
| Editorial scalability of evolutionary algorithms and other metaheuristics for large-scale continuous optimization problems | M Lozano, D Molina, F Herrera. | 2011 |
| A fast and scalable multi-objective genetic fuzzy system for linguistic fuzzy modeling in high-dimensional regression problems | R Alcalá, M Gacto, F Herrera. | 2011 |
| Differential evolution for optimizing the positioning of prototypes in nearest neighbor classification | I Triguero, S García, F Herrera. | 2011 |
| A methodology for Institution-Field ranking based on a bidimensional analysis: the IFQ 2 A index | D Torres-Salinas, JG Moreno-Torres, E Delgado-López-Cózar, F Herrera. | 2011 |
| Rankings ISI de las universidades españolas según campos científicos: descripción y resultados | D Torres-Salinas, E Delgado-López-Cózar, J García-Moreno, F Herrera. | 2011 |
| Hesitant fuzzy linguistic term sets | RM Rodríguez, L Martínez, F Herrera. | 2011 |
| A study of the scaling up capabilities of stratified prototype generation | I Triguero, J Derrac, F Herrera, S García. | 2011 |
| Enhancing IPADE algorithm with a different individual codification | I Triguero, S García, F Herrera. | 2011 |
| A preliminary study on the use of fuzzy rough set based feature selection for improving evolutionary instance selection algorithms | J Derrac, C Cornelis, S García, F Herrera. | 2011 |
| Rankings ISI de las universidades españolas según campos y disciplinas científicas (2011) | D Torres-Salinas, J García-Moreno-Torres, N Robinson-García, .... | 2011 |
| ISI rankings of universities in Spain by scientific field | D Torres-Salinas, E Delgado-Lopez-Cozar, J Garcia-Moreno-Torres, .... | 2011 |
| Special issue on the trends in applied intelligence systems | N García-Pedrajas, F Herrera, C Fyfe. | 2011 |
| Granularity based Instance Selection | N Verbiest, C Cornelis, F Herrera. | 2011 |
| Prototype Generation for Nearest Neighbor Classification: Survey of Methods | I Triguero, J Derrac, S Garcıa, F Herrera. | 2011 |
| On the Usefulness of Interval Valued Fuzzy Sets for Learning Fuzzy Rule Based Classification Systems | F Herrera. | 2011 |
| Estudio cuantitativo de la inducción electromagnética entre dos bobinas en función del número de espiras de una de ellas. | JMV Montoya, FJM Herrera, AN López, EA Garde, AB Vázquez. | 2011 |
| Aggregation schemes for binarization techniques Methods’ description | M Galar, A Fernández, E Barrenechea, H Bustince, F Herrera. | 2011 |
| Survey of New Approaches on Prototype Selection and Generation | J Derrac, I Triguero, S Garcıa, F Herrera. | 2011 |
| Dataset shift in classification: Approaches and problems | F Herrera. | 2011 |
| ISI rankings of Spanish universities according to fields and scientific disciplines (2011) | D Torres-Salinas, J García-Moreno-Torres, N Robinson-García, .... | 2011 |
| El poder de mercado, visto de la perspectiva del proceso de descubrimiento de mercado | F Herrera. | 2011 |
| NMEEF-SD: non-dominated multiobjective evolutionary algorithm for extracting fuzzy rules in subgroup discovery | CJ Carmona, P González, MJ del Jesus, F Herrera. | 2010 |
| A preliminary study on the selection of generalized instances for imbalanced classification | S García, J Derrac, I Triguero, C Carmona, F Herrera. | 2010 |
| Integration of an index to preserve the semantic interpretability in the multiobjective evolutionary rule selection and tuning of linguistic fuzzy systems | MJ Gacto, R Alcalá, F Herrera. | 2010 |
| Analysis of the performance of a semantic interpretability-based tuning and rule selection of fuzzy rule-based systems by means of a multi-objective evolutionary algorithm | MJ Gacto, R Alcalá, F Herrera. | 2010 |
| GP-COACH: Genetic Programming-based learning of COmpact and ACcurate fuzzy rule-based classification systems for High-dimensional problems | FJ Berlanga, AJ Rivera, MJ del Jesús, F Herrera. | 2010 |
| On the 2-tuples based genetic tuning performance for fuzzy rule based classification systems in imbalanced data-sets | A Fernández, MJ del Jesus, F Herrera. | 2010 |
| Multi-class imbalanced data-sets with linguistic fuzzy rule based classification systems based on pairwise learning | A Fernández, MJ Del Jesus, F Herrera. | 2010 |
| Analysing the hierarchical fuzzy rule based classification systems with genetic rule selection | A Fernández, MJ del Jesús, F Herrera. | 2010 |
| Prototype selection for nearest neighbor classification: Survey of methods | S Garcıa, J Derrac, JR Cano, F Herrera. | 2010 |
| A Review on Evolutionary Prototype Selection: An Empirical Study of Performance and Efficiency | S García, JR Cano, F Herrera. | 2010 |
| Introduction to the experimental design in the data mining tool KEEL | J Alcalá-Fdez, F Herrera, S García, MJ del Jesus, L Sánchez, .... | 2010 |
| Computing with words in decision support systems: an overview on models and applications | L Martınez, D Ruan, F Herrera. | 2010 |
| Advanced nonparametric tests for multiple comparisons in the design of experiments in computational intelligence and data mining: Experimental analysis of power | S García, A Fernández, J Luengo, F Herrera. | 2010 |
| Genetics-based machine learning for rule induction: state of the art, taxonomy, and comparative study | A Fernández, S García, J Luengo, E Bernadó-Mansilla, F Herrera. | 2010 |
| A study on the use of imputation methods for experimentation with Radial Basis Function Network classifiers handling missing attribute values: The good synergy between RBFNs … | J Luengo, S García, F Herrera. | 2010 |
| Domains of competence of fuzzy rule based classification systems with data complexity measures: A case of study using a fuzzy hybrid genetic based machine learning method | J Luengo, F Herrera. | 2010 |
| Geneticsbased machine learning for rule induction: Taxonomy, experimental study and state of the art | A Fernández, S García, J Luengo, E Bernadó-Mansilla, F Herrera. | 2010 |
| A first study on the noise impact in classes for fuzzy rule based classification systems | JA Sáez, J Luengo, F Herrera. | 2010 |
| An extraction method for the characterization of the Fuzzy Rule Based Classification Systems' behavior using data complexity measures: A case of study with FH-GBML | J Luengo, F Herrera. | 2010 |
| Analysis of the Effectiveness of the Genetic Algorithms based on Extraction of Association Rules | J Alcala-Fdez, N Flugy-Pape, A Bonarini, F Herrera. | 2010 |
| Genetic tuning of a laser pointer environment control device system for handicapped people with fuzzy systems | F Chávez, F Fernández, J Alcalá-Fdez, R Alcalá, F Herrera, G Olague. | 2010 |
| A fuzzy associative classification system with genetic rule selection for high-dimensional problems | J Alcalá-Fdéz, R Alcalá, F Herrera. | 2010 |
| A web based consensus support system for group decision making problems and incomplete preferences | S Alonso, E Herrera-Viedma, F Chiclana, F Herrera. | 2010 |
| q2-Index: Quantitative and qualitative evaluation based on the number and impact of papers in the Hirsch core | FJ Cabrerizo, S Alonso, E Herrera-Viedma, F Herrera. | 2010 |
| On the Use of Distributed Genetic Algorithms for the Tuning of Fuzzy Rule Based-Systems | I Robles, R Alcalá, J Benítez, F Herrera. | 2010 |
| WoS query partitioner: A tool to retrieve very large numbers of items from the Web of Science using different source‐based partitioning approaches | S Alonso, FJ Cabrerizo, E Herrera‐Viedma, F Herrera. | 2010 |
| Trends in applied intelligent system | N Garcaia-Pedrajas. | 2010 |
| Improving the performance of fuzzy rule-based classification systems with interval-valued fuzzy sets and genetic amplitude tuning | JA Sanz, A Fernández, H Bustince, F Herrera. | 2010 |
| Solving multi-class problems with linguistic fuzzy rule based classification systems based on pairwise learning and preference relations | A Fernández, M Calderón, E Barrenechea, H Bustince, F Herrera. | 2010 |
| A genetic algorithm for tuning fuzzy rule-based classification systems with interval-valued fuzzy sets | J Sanz, A Fernández, H Bustince, F Herrera. | 2010 |
| A genetic algorithm for feature selection and granularity learning in fuzzy rule-based classification systems for highly imbalanced data-sets | P Villar, A Fernández, F Herrera. | 2010 |
| A first approach for cost-sensitive classification with linguistic genetic fuzzy systems in imbalanced data-sets | V López, A Fernández, F Herrera. | 2010 |
| USING SIMILARITY MEASURES IN FUZZY RULE-BASED CLASSIFICATION SYSTEMS WITH INTERVAL-VALUED FUZZY SETS | J Sanz, D Jurío, A Fernández, F Herrera, H Bustince. | 2010 |
| An approach for detecting, quantifying, and visualizing the evolution of a research field: A practical application to the fuzzy sets theory field | MJ Cobo, AG López-Herrera, E Herrera-Viedma, F Herrera. | 2010 |
| A bibliometric study about the research based on hybridating the fuzzy logic field and the other computational intelligent techniques: A visual approach | AG López-Herrera, MJ Cobo, E Herrera-Viedma, F Herrera. | 2010 |
| Memetic algorithms for continuous optimisation based on local search chains | D Molina, M Lozano, C García-Martínez, F Herrera. | 2010 |
| Visualization and Evolution of the Scientific Structure of Fuzzy Sets Based Research in Spain | AG Lopez-Herrera, MJ Cobo, E Herrera-Viedma, F Herrera, .... | 2010 |
| MA-SW-Chains: Memetic algorithm based on local search chains for large scale continuous global optimization | D Molina, M Lozano, F Herrera. | 2010 |
| Test suite for the special issue of soft computing on scalability of evolutionary algorithms and other metaheuristics for large scale continuous optimization problems | F Herrera, M Lozano, D Molina. | 2010 |
| Components and parameters of de, real-coded chc, and g-cmaes | F Herrera, M Lozano, D Molina. | 2010 |
| hg-index: A new index to characterize the scientific output of researchers based on the h-and g-indices | S Alonso, FJ Cabrerizo, E Herrera-Viedma, F Herrera. | 2010 |
| A survey on evolutionary instance selection and generation | J Derrac, S García, F Herrera. | 2010 |
| IFS-CoCo: Instance and feature selection based on cooperative coevolution with nearest neighbor rule | J Derrac, S García, F Herrera. | 2010 |
| Analysis of the efficacy of a Two-Stage methodology for ant colony optimization: Case of study with TSP and QAP | A Puris, R Bello, F Herrera. | 2010 |
| IPADE: Iterative prototype adjustment for nearest neighbor classification | I Triguero, S García, F Herrera. | 2010 |
| Stratified prototype selection based on a steady-state memetic algorithm: a study of scalability | J Derrac, S García, F Herrera. | 2010 |
| A preliminary study on the use of differential evolution for adjusting the position of examples in nearest neighbor classification | I Triguero, S García, F Herrera. | 2010 |
| IFS-CoCo in the landscape contest: description and results | J Derrac, S García, F Herrera. | 2010 |
| A preliminary study on overlapping and data fracture in imbalanced domains by means of genetic programming-based feature extraction | JG Moreno-Torres, F Herrera. | 2010 |
| Genetics-based machine learning for rule induction: Taxonomy, experimental study and state of the art | A Fernández, S García, J Luengo, E Bernadó-Mansilla, F Herrera. | 2010 |
| GUEST EDITORS'INTRODUCTION: SPECIAL ISSUE ON INTELLIGENT SYSTEMS DESIGN AND APPLICATIONS (ISDA'2009) | F Herrera, F Marcelloni, V Loia. | 2010 |
| Special Issue on Decision Support Systems based on Computing with Words: Applications | F Herrera, L Martínez. | 2010 |
| Genetic fuzzy systems for subgroup discovery. Models and applications | F Herrera. | 2010 |
| Determinando Automáticamente los Dominios de Competencia de un Sistema de Clasificación Basado en Reglas Difusas: Un Caso de Estudio con FH-GBML | J Luengo, F Herrera. | 2010 |
| Obtención de los dominios de competencia de C4. 5 por medio de medidas de separabilidad de clases | J Luengo, F Herrera. | 2010 |
| Trends in Applied Intelligent Systems | F Herrera, C Fyfe, JM Benítez, M Ali. | 2010 |
| Un primer estudio sobre el uso de aprendizaje sensible al coste con sistemas de clasificación basados en reglas difusas para problemas no balanceados | V López, A Fernández, F Herrera. | 2010 |
| Proceedings of the 23rd International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems-Volume Part I.: Volume Part I | N García-Pedrajas. | 2010 |
| Call for papers: Special issue of soft computing: A fusion of foundations, methodologies and applications on scalability of evolutionary algorithms and other metaheuristics for … | M Lozano, F Herrera. | 2010 |
| Results of adrenal surgery. Data of a Spanish National Survey | JM Villar, P Moreno, J Ortega, E Bollo, CP Ramírez, N Muñoz, C Martínez, .... | 2010 |
| Non-dominated multi-objective evolutionary algorithm based on fuzzy rules extraction for subgroup discovery | CJ Carmona, P González, MJ del Jesús, F Herrera. | 2009 |
| An analysis of evolutionary algorithms with different types of fuzzy rules in subgroup discovery | CJ Carmona, P González, MJ del Jesus, F Herrera. | 2009 |
| Learning the membership function contexts for mining fuzzy association rules by using genetic algorithms | J Alcalá-Fdez, R Alcalá, MJ Gacto, F Herrera. | 2009 |
| Adaptation and application of multi-objective evolutionary algorithms for rule reduction and parameter tuning of fuzzy rule-based systems | MJ Gacto, R Alcalá, F Herrera. | 2009 |
| Improving fuzzy logic controllers obtained by experts: a case study in HVAC systems | R Alcalá, J Alcalá-Fdez, MJ Gacto, F Herrera. | 2009 |
| A Multiobjective Evolutionary Algorithm for Tuning Fuzzy Rule Based Systems with Measures for Preserving Interpretability. | MJ Gacto, R Alcalá, F Herrera. | 2009 |
| Handling High-Dimensional Regression Problems by Means of an Efficient Multi-Objective Evolutionary Algorithm | MJ Gacto, R Alcalá, F Herrera. | 2009 |
| Evolutionary algorithms for subgroup discovery in e-learning: A practical application using Moodle data | C Romero, P González, S Ventura, MJ Del Jesús, F Herrera. | 2009 |
| KEEL: a software tool to assess evolutionary algorithms for data mining problems | J Alcalá-Fdez, L Sanchez, S Garcia, MJ del Jesus, S Ventura, JM Garrell, .... | 2009 |
| Hierarchical fuzzy rule based classification systems with genetic rule selection for imbalanced data-sets | A Fernández, MJ del Jesus, F Herrera. | 2009 |
| On the influence of an adaptive inference system in fuzzy rule based classification systems for imbalanced data-sets | A Fernández, MJ del Jesus, F Herrera. | 2009 |
| Improving the performance of fuzzy rule based classification systems for highly imbalanced data-sets using an evolutionary adaptive inference system | A Fernández, MJ del Jesus, F Herrera. | 2009 |
| Genetic Cooperative-Competitive Fuzzy Rule Based Learning Method using Genetic Programming for Highly Imbalanced Data-Sets. | A Fernández, FJ Berlanga, MJ del Jesús, F Herrera. | 2009 |
| A fuzzy model to evaluate the suitability of installing an enterprise resource planning system | PJ Sánchez, L Martı, C Garcı, F Herrera, E Herrera-Viedma. | 2009 |
| A fuzzy model to evaluate the suitability of installing an ERP system | PJ Sįnchez, L Martınez, C Garcıa, F Herrera, E Herrera-Viedma. | 2009 |
| Linguistic decision making: Tools and applications | L Martínez, D Ruan, F Herrera, E Herrera-Viedma, PP Wang. | 2009 |
| A study of statistical techniques and performance measures for genetics-based machine learning: accuracy and interpretability | S García, A Fernández, J Luengo, F Herrera. | 2009 |
| A study on the use of statistical tests for experimentation with neural networks: Analysis of parametric test conditions and non-parametric tests | J Luengo, S García, F Herrera. | 2009 |
| A first approach to nearest hyperrectangle selection by evolutionary algorithms | S García, J Derrac, J Luengo, F Herrera. | 2009 |
| Addressing data-complexity for imbalanced data-sets: A preliminary study on the use of preprocessing for c4. 5 | J Luengo, A Fernández, S García, F Herrera. | 2009 |
| Implementation and integration of algorithms into the KEEL data-mining software tool | A Fernández, J Luengo, J Derrac, J Alcalá-Fdez, F Herrera. | 2009 |
| On the use of Measures of Separability of Classes to Characterise the Domains of Competence of a Fuzzy Rule Based Classification System. | J Luengo, F Herrera. | 2009 |
| Domains of competence of artificial neural networks using measures of separability of classes | J Luengo, F Herrera. | 2009 |
| Evolutionary extraction of association rules: A preliminary study on their effectiveness | NF Papè, J Alcalá-Fdez, A Bonarini, F Herrera. | 2009 |
| A multiobjective evolutionary approach to concurrently learn rule and data bases of linguistic fuzzy-rule-based systems | R Alcalá, P Ducange, F Herrera, B Lazzerini, F Marcelloni. | 2009 |
| Evolutionary parallel and gradually distributed lateral tuning of fuzzy rule-based systems | I Robles, R Alcalá, JM Benítez, F Herrera. | 2009 |
| Generating single granularity-based fuzzy classification rules for multiobjective genetic fuzzy rule selection | R Alcalá, Y Nojima, F Herrera, H Ishibuchi. | 2009 |
| h-Index: A review focused in its variants, computation and standardization for different scientific fields | S Alonso, FJ Cabrerizo, E Herrera-Viedma, F Herrera. | 2009 |
| Computing with words in decision making: foundations, trends and prospects | F Herrera, S Alonso, F Chiclana, E Herrera-Viedma. | 2009 |
| Group decision making with incomplete fuzzy linguistic preference relations | S Alonso, FJ Cabrerizo, F Chiclana, F Herrera, E Herrera‐Viedma. | 2009 |
| Individual and social strategies to deal with ignorance situations in multi-person decision making | S Alonso, E Herrera-Viedma, F Chiclana, F Herrera. | 2009 |
| Distributed Genetic Tuning of Fuzzy Rule-Based Systems. | I Robles, R Alcalá, JM Benítez, F Herrera. | 2009 |
| Computing with words and decision making | F Herrera, E Herrera-Viedma, S Alonso, F Chiclana. | 2009 |
| Agregación de índices bibliométricos para evaluar la producción científica de los investigadores | F Herrera, E Herrera-Viedma, S Alonso, FJ Cabrerizo. | 2009 |
| Aggregation of bibliometric indices to evaluate the scientific production of researchers | F Herrera, E Herrera-Viedma, S Alonso, FJ Cabrerizo. | 2009 |
| Learning consistent, complete and compact sets of fuzzy rules in conjunctive normal form for regression problems | J Casillas, P Martínez, AD Benítez. | 2009 |
| Enhancing the effectiveness and interpretability of decision tree and rule induction classifiers with evolutionary training set selection over imbalanced problems | S García, A Fernández, F Herrera. | 2009 |
| Enhancing fuzzy rule based systems in multi-classification using pairwise coupling with preference relations | A Fernández, M Calderón, E Barrenechea, H Bustince, F Herrera. | 2009 |
| A genetic learning of the fuzzy rule-based classification system granularity for highly imbalanced data-sets | P Villar, A Fernández, F Herrera. | 2009 |
| A First Study on the Use of Interval-Valued Fuzzy Sets with Genetic Tuning for Classification with Imbalanced Data-Sets | J Sanz, A Fernández, H Bustince, F Herrera. | 2009 |
| Un algoritmo genético para selección de características en sistemas de clasificación basados en reglas difusas para conjuntos de datos altamente no balanceados | P Villar, A Fernández, A Sánchez, F Herrera. | 2009 |
| A study on the use of non-parametric tests for analyzing the evolutionary algorithms’ behaviour: a case study on the CEC’2005 special session on real parameter optimization | S García, D Molina, M Lozano, F Herrera. | 2009 |
| Applying multi-objective evolutionary algorithms to the automatic learning of extended Boolean queries in fuzzy ordinal linguistic information retrieval systems | AG López-Herrera, E Herrera-Viedma, F Herrera. | 2009 |
| A study of the use of multi‐objective evolutionary algorithms to learn Boolean queries: A comparative study | AG López‐Herrera, E Herrera‐Viedma, F Herrera. | 2009 |
| Hybrid crossover operators with multiple descendents for real‐coded genetic algorithms: Combining neighborhood‐based crossover operators | AM Sánchez, M Lozano, P Villar, F Herrera. | 2009 |
| A memetic algorithm using local search chaining for black-box optimization benchmarking 2009 for noisy functions | D Molina, M Lozano, F Herrera. | 2009 |
| A memetic algorithm using local search chaining forblack-box optimization benchmarking 2009 for noise free functions | D Molina, M Lozano, F Herrera. | 2009 |
| Study of the influence of the local search method in memetic algorithms for large scale continuous optimization problems | D Molina, M Lozano, F Herrera. | 2009 |
| A survey on the application of genetic programming to classification | PG Espejo, S Ventura, F Herrera. | 2009 |
| Evolutionary undersampling for classification with imbalanced datasets: Proposals and taxonomy | S García, F Herrera. | 2009 |
| A first study on the use of coevolutionary algorithms for instance and feature selection | J Derrac, S García, F Herrera. | 2009 |
| Memetic algorithm with local search chaining for continuous optimization problems: A scalability test | D Molina, M Lozano, F Herrera. | 2009 |
| Visualization and evolution of the scientific structure of fuzzy sets research in Spain | AG López-Herrera, MJ Cobos, EH Viedma, F Herrera, RB Moreno, .... | 2009 |
| Diagnose of effective evolutionary prototype selection using an overlapping measure | S García, JR Cano, E Bernadó-Mansilla, F Herrera. | 2009 |
| Estudio del desempeño de la optimización basada en mallas variables en problemas con óptimos en las fronteras del espacio búqueda | R Navarro, A Puris, R Bello, F Herrera. | 2009 |
| Foundations of Computational Intelligence Volume 2: Approximate Reasoning | AE Hassanien, A Abraham, F Herrera. | 2009 |
| Algoritmos genéticos multimodales: un estudio sobre la parametrización del método clearing aplicado al problema “Job Shop” | ME Pérez, F Herrera. | 2009 |
| ACOR hıbrido con múltiples colonias para problemas de optimización continua | C Blum, P Cardoso, F Herrera. | 2009 |
| Un algoritmo genético para selección de caracterí¿ sticas en sistemas de clasificación basados en reglas difusas para conjuntos de datos altamente no balanceados | P Villar, A Fernández, A Sánchez, F Herrera. | 2009 |
| Data mining and hybrid intelligent systems | F Xhafa, F Herrera, M Köppen. | 2009 |
| Study of the Influence of the Local Search Method in Memetic Algorithms for Large Scale Continuous Optimization Problems. | D Molina, M Lozano, F Herrera. | 2009 |
| A Study of | S Garcia, A Fernandez, G Luengo, F Herrera. | 2009 |
| Fuzzy evolutionary algorithms and genetic fuzzy systems: a positive collaboration between evolutionary algorithms and fuzzy systems | F Herrera, M Lozano. | 2009 |
| Sensor virtual adaptable de concentración de etanol para Fermentadores Industriales | B Martínez, F Herrera, L Peralta. | 2009 |
| Agregación de índices bibliométricos para evaluar la producción científica de los investigadores. | F Herrera, E Herrera-Viedma, S Alonso, FJ Cabrerizo. | 2009 |
| Linguistic decision making: tools and applications: preface | L Martínez, D Ruan, F Herrera, E Herrera-Viedma, PP Wang. | 2009 |
| An improved multi-objective genetic algorithm for tuning linguistic fuzzy systems | MJ Gacto, R Alcalá, F Herrera. | 2008 |
| On the usefulness of MOEAs for getting compact FRBSs under parameter tuning and rule selection | R Alcalá, J Alcalá-Fdez, MJ Gacto, F Herrera. | 2008 |
| Multi-objective genetic fuzzy systems: on the necessity of including expert knowledge in the MOEA design process | MJ Gacto, R Alcala, F Herrera. | 2008 |
| Subgroup Discovery with Linguistic Rules | MJ Del Jesus, P González, F Herrera. | 2008 |
| Special issue on fuzzy approaches in preference modelling, decision making and applications | F Chiclana, E Herrera-Viedma, S Alonso, F Herrera, J Yañez, J Montero, .... | 2008 |
| A study of the behaviour of linguistic fuzzy rule based classification systems in the framework of imbalanced data-sets | A Fernández, S García, MJ del Jesus, F Herrera. | 2008 |
| A memetic algorithm for evolutionary prototype selection: A scaling up approach | S García, JR Cano, F Herrera. | 2008 |
| Replacement strategies to preserve useful diversity in steady-state genetic algorithms | M Lozano, F Herrera, JR Cano. | 2008 |
| Subgroup discover in large size data sets preprocessed using stratified instance selection for increasing the presence of minority classes | JR Cano, S García, F Herrera. | 2008 |
| KEEL: A data mining software tool integrating genetic fuzzy systems | J Alcalá-Fdez, S García, FJ Berlanga, A Fernández, L Sánchez, .... | 2008 |
| Making CN2-SD subgroup discovery algorithm scalable to large size data sets using instance selection | JR Cano, F Herrera, M Lozano, S García. | 2008 |
| A novel genetic cooperative-competitive fuzzy rule based learning method using genetic programming for high dimensional problems | FJ Berlanga, MJ del Jesus, F Herrera. | 2008 |
| A short study on the use of genetic 2-tuples tuning for fuzzy rule based classification systems in imbalanced data-sets | A Fernández, MJ del Jesus, F Herrera. | 2008 |
| Sistemas Basados en Reglas Difusas en Clasificación: Nuevos Retos | AF Hilario, MJ del Jesus, F Herrera. | 2008 |
| A consistency‐based procedure to estimate missing pairwise preference values | S Alonso, F Chiclana, F Herrera, E Herrera‐Viedma, J Alcalá‐Fdez, .... | 2008 |
| A fuzzy linguistic methodology to deal with unbalanced linguistic term sets | F Herrera, E Herrera-Viedma, L Martínez. | 2008 |
| Cardinal consistency of reciprocal preference relations: a characterization of multiplicative transitivity | F Chiclana, E Herrera-Viedma, S Alonso, F Herrera. | 2008 |
| Knowledge base learning of linguistic fuzzy rule-based systems in a multi-objective evolutionary framework | P Ducange, R Alcalá, F Herrera, B Lazzerini, F Marcelloni. | 2008 |
| A note on the estimation of missing pairwise preference values: a uninorm consistency based method | F Chiclana, E Herrera-Viedma, S Alonso, F Herrera. | 2008 |
| Construction of consistent fuzzy preference relations using uninorms | F Chiclana, S Alonso, E Herrera-Viedma, F Herrera. | 2008 |
| Guest editors' introduction: special issue on fuzzy approaches in preference modelling, decision making and applications | F Chiclana, E Herrera-Viedma, S Alonso, F Herrera. | 2008 |
| Eighth International Conference on Hybrid Intelligent Systems | F Xhafa, F Herrera, A Abraham, M Köppen, JM Bénitez. | 2008 |
| A Multiobjective Evolutionary Conceptual Clustering Methodology for Gene Annotation Within Structural Databases: A Case of Study on the Gene Ontology Database | RC Romero-Zaliz, C Rubio-Escudero, JP Cobb, F Herrera, O Cordón, .... | 2008 |
| A multiobjective evolutionary algorithm for spam e-mail filtering | AG López-Herrera, E Herrera-Viedma, F Herrera. | 2008 |
| Global and local real-coded genetic algorithms based on parent-centric crossover operators | C García-Martínez, M Lozano, F Herrera, D Molina, AM Sánchez. | 2008 |
| Visualizing the Hybridizations between the Fuzzy Logic Field and the Other Soft-Computing Techniques | AG López-Herrera, MJ Cobo, E Herrera-Viedma, F Herrera. | 2008 |
| Real‐parameter crossover operators with multiple descendents: An experimental study | AM Sánchez, M Lozano, C García‐Martínez, D Molina, F Herrera. | 2008 |
| Memetic algorithm for intense local search methods using local search chains | D Molina, M Lozano, C García-Martínez, F Herrera. | 2008 |
| An extension on statistical comparisons of classifiers over multiple data sets for all pairwise comparisons | S Garcıa, F Herrera. | 2008 |
| Genetic fuzzy systems: taxonomy, current research trends and prospects | F Herrera. | 2008 |
| An interactive decision support system based on consistency criteria | S Alonso, FJ Cabrerizo, F Chiclana, F Herrera, E Herrera-Viedma. | 2008 |
| Evolutionary training set selection to optimize c4. 5 in imbalanced problems | S García, F Herrera. | 2008 |
| Design of experiments in computational intelligence: on the use of statistical inference | S García, F Herrera. | 2008 |
| Improvement to the cooperative rules methodology by using the ant colony system algorithm | R Alcalá, J Casillas, O Cordón, F Herrera. | 2008 |
| Fuzzy Sets and Their Extensions: Representation, Aggregation and Models-Intelligent Systems from Decision Making to Data Mining, Web Intelligence and Computer Vision | HB Sola, F Herrera, J Montero. | 2008 |
| Special Issue on Fuzzy Approaches in Preference Modelling, Decision Making and Applications INTRODUCTION | F Chiclana, E Herrera-Viedma, S Alonso, F Herrera. | 2008 |
| Evaluación del exudado gomoso de Acacia siamea como coagulante en la clarificación de las aguas para consumo humano | A Fernández, F Herrera, M Mas y Rubí, D Mejías, A Diaz. | 2008 |
| Método de Agrupamiento en Línea para la Identificación de Modelos Borrosos Takagi-Sugeno | B Martínez, F Herrera, J Fernández, E Marichal. | 2008 |
| An incremental clustering method and its application in online fuzzy modeling | B Martínez, F Herrera, J Fernández, E Marichal. | 2008 |
| Genetic fuzzy systems: taxonomy, current research trends and prospects, Evolutionary Intelligence | F Herrera. | 2008 |
| A multi-objective genetic algorithm for tuning and rule selection to obtain accurate and compact linguistic fuzzy rule-based systems | R Alcalá, MJ Gacto, F Herrera, J Alcalá-Fdez. | 2007 |
| Rule base reduction and genetic tuning of fuzzy systems based on the linguistic 3-tuples representation | R Alcalá, J Alcalá-Fdez, MJ Gacto, F Herrera. | 2007 |
| Genetic learning of membership functions for mining fuzzy association rules | R Alcalá, J Alcalá-Fdez, MJ Gacto, F Herrera. | 2007 |
| A multi-objective evolutionary algorithm for rule selection and tuning on fuzzy rule-based systems | R Alcalá, J Alcalá-Fdez, MJ Gacto, F Herrera. | 2007 |
| Evolutionary fuzzy rule induction process for subgroup discovery: a case study in marketing | MJ Del Jesus, P González, F Herrera, M Mesonero. | 2007 |
| Multiobjective genetic algorithm for extracting subgroup discovery fuzzy rules | MJ del Jesus, P González, F Herrera. | 2007 |
| Preface: Special Issue on Genetic Fuzzy Systems and the Interpretability–Accuracy Trade-off | J Casillas, F Herrera, R Pérez, MJ del Jesus, P Villar. | 2007 |
| Niching genetic feature selection algorithms applied to the design of fuzzy rule-based classification systems | JJ Aguilera, M Chica, MJ del Jesus, F Herrera. | 2007 |
| Evolutionary stratified training set selection for extracting classification rules with trade off precision-interpretability | JR Cano, F Herrera, M Lozano. | 2007 |
| An analysis of the rule weights and fuzzy reasoning methods for linguistic rule based classification systems applied to problems with highly imbalanced data sets | A Fernández, S García, F Herrera, MJ del Jesús. | 2007 |
| Un algoritmo memético para selección de prototipos: Una propuesta eficiente para problemas de tamano medio | S Garcıa, JR Cano, F Herrera. | 2007 |
| Fuzzy Machine Learning-An Analysis of the Rule Weights and Fuzzy Reasoning Methods for Linguistic Rule Based Classification Systems Applied to Problems with Highly Imbalanced … | A Fernandez, S Garcia, F Herrera, MJ Jesus. | 2007 |
| A study on the use of statistical tests for experimentation with neural networks | J Luengo, S García, F Herrera. | 2007 |
| A proposal for the genetic lateral tuning of linguistic fuzzy systems and its interaction with rule selection | R Alcalá, J Alcalá-Fdez, F Herrera. | 2007 |
| Genetic learning of accurate and compact fuzzy rule based systems based on the 2-tuples linguistic representation | R Alcalá, J Alcalá-Fdez, F Herrera, J Otero. | 2007 |
| Local identification of prototypes for genetic learning of accurate TSK fuzzy rule‐based systems | R Alcalá, J Alcalá‐Fdez, J Casillas, O Cordón, F Herrera. | 2007 |
| Increasing fuzzy rules cooperation based on evolutionary adaptive inference systems | J Alcalá‐Fdez, F Herrera, F Márquez, A Peregrín. | 2007 |
| A consensus model for group decision making with incomplete fuzzy preference relations | F Chiclana, S Alonso, F Herrera, E Herrera-Viedma. | 2007 |
| Group decision-making model with incomplete fuzzy preference relations based on additive consistency | E Herrera-Viedma, F Chiclana, F Herrera, S Alonso. | 2007 |
| Some induced ordered weighted averaging operators and their use for solving group decision-making problems based on fuzzy preference relations | F Chiclana, E Herrera-Viedma, F Herrera, S Alonso. | 2007 |
| Visualizing consensus in group decision making situations | S Alonso, E Herrera-Viedma, FJ Cabrerizo, F Chiclana, F Herrera. | 2007 |
| Consistency of reciprocal preference relations | F Chiclana, E Herrera-Viedma, S Alonso, F Herrera. | 2007 |
| Statistical comparisons by means of non-parametric tests: a case study on genetic based machine learning | S García, AD Benítez, F Herrera, A Fernández. | 2007 |
| A taxonomy and an empirical analysis of multiple objective ant colony optimization algorithms for the bi-criteria TSP | C García-Martínez, O Cordón, F Herrera. | 2007 |
| Un estudio experimental sobre el uso de test no paramétricos para analizar el comportamiento de los algoritmos evolutivos en problemas de optimización | S García, D Molina, M Lozano, F Herrera. | 2007 |
| Tests no paramétricos de comparaciones múltiples con algoritmo de control en el análisis de algoritmos evolutivos: Un caso de estudio con los resultados de la sesión especial … | S García, D Molina, M Lozano, F Herrera. | 2007 |
| Algoritmo Memético con Intensidad de Búsqueda Local Adaptativa | D Molina, F Herrera, M Lozano. | 2007 |
| Fuzzy Sets and Their Extensions: Representation, Aggregation and Models: Intelligent Systems from Decision Making to Data Mining, Web Intelligence and Computer Vision | H Bustince, F Herrera, J Montero. | 2007 |
| Cooperative evolutionary learning of linguistic fuzzy rules and parametric aggregation connectors for Mamdani fuzzy systems | FA Márquez, A Peregrín, F Herrera. | 2007 |
| Algoritmos Genéticos con Codificación Real: Operadores de Cruce Híbridos Basados en Entornos con Múltiples Descendientes | F Herrera, M Lozano, AM Sánchez. | 2007 |
| Fuzzy Systems-A Study on the Use of the Fuzzy Reasoning Method Based on the Winning Rule vs. Voting Procedure for Classification with Imbalanced Data Sets | A Fernandez, S Garcia, MJ Jesus, F Herrera. | 2007 |
| Algoritmos genéticos para codificación real con operador de cruce híbrido con múltiples descendientes: 2blx0. 5-2fr0. 5-2pnx3-2sbx0. 01 | AM Sánchez, M Lozano, F Herrera. | 2007 |
| A genetic-programming-based approach for the learning of compact fuzzy rule-based classification systems | FJ Berlanga, MJ del Jesús, MJ Gacto, F Herrera. | 2006 |
| Fuzzy rule reduction and tuning of fuzzy logic controllers for a HVAC system | R Alcalá, J Alcalá-Fdez, MJ Gacto, F Herrera. | 2006 |
| Genetic lateral and amplitude tuning with rule selection for fuzzy control of heating, ventilating and air conditioning systems | R Alcalá, J Alcala-Fdez, FJ Berlanga, MJ Gacto, F Herrera. | 2006 |
| Multiobjective evolutionary induction of subgroup discovery fuzzy rules: a case study in marketing | F Berlanga, MJ Del Jesus, P González, F Herrera, M Mesonero. | 2006 |
| On the combination of evolutionary algorithms and stratified strategies for training set selection in data mining | JR Cano, F Herrera, M Lozano. | 2006 |
| A proposal of evolutionary prototype selection for class imbalance problems | S García, JR Cano, A Fernández, F Herrera. | 2006 |
| Técnicas de reducción de datos en KDD. El uso de Algoritmos Evolutivos para la Selección de Instancias | F Herrera, JR Cano. | 2006 |
| A First Study on the Use of Fuzzy Rule Based Classification Systems for Problems with Imbalanced Data Sets | MJ del Jesus, A Fernández, S Garcıa, F Herrera. | 2006 |
| Incorporating knowledge in evolutionary prototype selection | S García, JR Cano, F Herrera. | 2006 |
| UN PRIMER ESTUDIO SOBRE EL USO DE LOS SISTEMAS DE CLASIFICACIÓN BASADOS EN REGLAS DIFUSAS EN PROBLEMAS DE CLASIFICACIÓN CON CLASES NO BALANCEADAS | AF Hilario, S García, F Herrera, MJ del Jesus. | 2006 |
| Strategies to manage ignorance situations in multiperson decision making problems | S Alonso, E Herrera-Viedma, F Chiclana, F Herrera, C Porcel. | 2006 |
| Recent advancements of fuzzy sets: Theory and practice | F Herrera, E Herrera-Viedma, L Martínez, PP Wang. | 2006 |
| Hybrid learning models to get the interpretability–accuracy trade-off in fuzzy modeling | R Alcalá, J Alcalá-Fdez, J Casillas, O Cordón, F Herrera. | 2006 |
| Guest editorial: Recent advancements of fuzzy sets: Theory and practice | F Herrera, E Herrera-Viedma, L Martínez, PP Wang. | 2006 |
| A multi-granular linguistic hierarchical model to evaluate the quality of web site services | F Herrera, E Herrera-Viedma, L Martínez, LG Pérez, AG López-Herrera, .... | 2006 |
| A decision aid system to provide consistent linguistic preference relations | S Alonso, E Herrera-Viedma, F Herrera, FJ Cabrerizo, F Chiclana. | 2006 |
| Continuous scatter search: an analysis of the integration of some combination methods and improvement strategies | F Herrera, M Lozano, D Molina. | 2006 |
| Hybrid learning models to get the interpretabilityÔÇôaccuracy trade-off in fuzzy modeling | R Alcal├ í, J Alcal├ í-Fdez, J Casillas, O Cord├│ n, F Herrera. | 2006 |
| New trends in fuzzy modeling. part II: applications | AM Alimi, F Herrera. | 2006 |
| New trends in the fuzzy modeling part I: novel approaches | AM Alimi, F Herrera. | 2006 |
| Special Issue on Genetic Fuzzy Systems and the Interpretability–Accuracy Trade-off | J Casillas Barranquero, F Herrera Triguero, FGR Pérez Rodríguez, .... | 2006 |
| Métodos de agrupamiento clásico para el modelado difuso en línea | B Martínez, F Herrera, JA Fernández. | 2006 |
| Genetic lateral and amplitude tuning of membership functions for fuzzy systems | R Alcalá, J Alcalá-Fdez, MJ Gacto, F Herrera. | 2005 |
| Evolutionary induction of descriptive rules in a market problem | MJ del Jesús, P González, F Herrera, M Mesonero. | 2005 |
| Multiobjective evolutionary induction of subgroup discovery rules in a market problem | F Berlanga, MJ del Jesus, P González, F Herrera. | 2005 |
| Inducción evolutiva multiobjetivo de reglas de descripción de subgrupos en un problema de marketing | MJ del Jesus, P González, F Herrera. | 2005 |
| Genetic tuning of fuzzy rule deep structures preserving interpretability and its interaction with fuzzy rule set reduction | J Casillas, O Cordón, MJ Del Jesus, F Herrera. | 2005 |
| Stratification for scaling up evolutionary prototype selection | JR Cano, F Herrera, M Lozano. | 2005 |
| Replacement strategies to maintain useful diversity in steady-state genetic algorithms | M Lozano, F Herrera, JR Cano. | 2005 |
| A study on the combination of evolutionary algorithms and stratified strategies for training set selection in data mining | JR Cano, F Herrera, M Lozano. | 2005 |
| Strategies for scaling up evolutionary instance reduction algorithms for data mining | JR Cano, F Herrera, M Lozano. | 2005 |
| Instance selection using evolutionary algorithms: an experimental study | JR Cano, F Herrera, M Lozano. | 2005 |
| Genetic tuning of fuzzy rule deep structures for linguistic modeling | J Casillas, O Cordon, MJ Del Jesus, F Herrera. | 2005 |
| Learning fuzzy rules using Genetic Programming: Context-free grammar definition for high-dimensionality problems | FJ Berlanga, MJ Del Jesus, F Herrera. | 2005 |
| Learning compact fuzzy rule-based classification systems with genetic programming. | FJ Berlanga, MJ del Jesus, F Herrera. | 2005 |
| Aprendizaje de reglas difusas mediante programación genética en problemas con alta dimensionalidad | FJ Berlanga, MJ del Jesus, F Herrera. | 2005 |
| Managing non-homogeneous information in group decision making | F Herrera, L Martınez, PJ Sánchez. | 2005 |
| A multigranular hierarchical linguistic model for design evaluation based on safety and cost analysis | L Martínez, J Liu, JB Yang, F Herrera. | 2005 |
| Genetic learning of the knowledge base of a fuzzy system by using the linguistic 2-tuples representation | R Alcalá, J Alcalá-Fdez, F Herrera, J Otero. | 2005 |
| A genetic rule weighting and selection process for fuzzy control of heating, ventilating and air conditioning systems | R Alcalá, J Casillas, O Cordón, A González, F Herrera. | 2005 |
| A new genetic fuzzy system based on linguistic 2-tuples to learn knowledge bases | R Alcalá, J Alcalá-Fdez, F Herrera, J Otero. | 2005 |
| Integrating evolutionary computation components in ant colony optimization | S Alonso, O Cordón, IF de Viana, F Herrera. | 2005 |
| Learning cooperative linguistic fuzzy rules using the best–worst ant system algorithm | J Casillas, O Cordón, I Fernández de Viana, F Herrera. | 2005 |
| Hybrid crossover operators for real-coded genetic algorithms: an experimental study | F Herrera, M Lozano, AM Sánchez. | 2005 |
| Adaptive local search parameters for real-coded memetic algorithms | D Molina, F Herrera, M Lozano. | 2005 |
| Genetic fuzzy systems: Status, critical considerations and future directions | F Herrera. | 2005 |
| Extracción de modelos predictivos e interpretables en conjuntos de datos de tamaño grande mediante la selección de conjuntos de entrenamiento | JR Cano, F Herrera, M Lozano. | 2005 |
| Evolutionary inducción of descriptive fuzzy rules in a market problem | MJ Del Jesus, P González, F Herrera, M Mesonero. | 2005 |
| Editorial Real coded genetic algorithms | F Herrera, M Lozano. | 2005 |
| Proyecto KEEL: Desarrollo de una herramienta para el análisis e implementación de algoritmos de extracción de conocimiento evolutivos | J Alcalá-Fdez, MJ del Jesus, JM Garrell, F Herrera, C Herbás, L Sánchez. | 2004 |
| Evolutionary stratified instance selection applied to training set selection for extracting high precise-interpretable classification rules | JR Cano, F Herrera, M Lozano. | 2004 |
| A multi-granular linguistic decision model for evaluating the quality of network services | F Herrera, E Herrera-Viedma, L Martínez, F Mata, PJ Sánchez. | 2004 |
| Incorporating filtering techniques in a fuzzy linguistic multi-agent model for information gathering on the web | F Herrera, E Herrera-Viedma, L Martínez, JC Herrera, AG López Herrera. | 2004 |
| Genetic tuning on fuzzy systems based on the linguistic 2-tuples representation | R Alcala, F Herrera. | 2004 |
| Induced ordered weighted geometric operators and their use in the aggregation of multiplicative preference relations | F Chiclana, E Herrera‐Viedma, F Herrera, S Alonso. | 2004 |
| A learning procedure to estimate missing values in fuzzy preference relations based on additive consistency | S Alonso, F Chiclana, F Herrera, E Herrera-Viedma. | 2004 |
| A Group Decision Making Model with Incomplete Fuzzy Preference Relations Based on Additive Consistency | S Alonso, F Chiclana, F Herrera, E Herrera-Viedma. | 2004 |
| Additive consistency as a tool to solve group decision making problems | F Chiclana, S Alonso, F Herrera, E Herrera-Viedma. | 2004 |
| Accuracy improvements in linguistic fuzzy modeling | F Herrera, O Cordon, L Magdalena, J Casillas. | 2004 |
| A hybrid learning process for the knowledge base of a fuzzy rule-based system | J Casillas, O Cordón, F Herrera, P Villar. | 2004 |
| Aprendizaje híbrido de la base de conocimiento de un sistema basado en reglas difusas mediante algoritmos genéticos y colonias de hormigas | J Casillas, O Cordón, F Herrera, P Villar. | 2004 |
| Ten years of genetic fuzzy systems: current framework and new trends | O Cordón, F Herrera, F Gomide, F Hoffmann, L Magdalena. | 2004 |
| An empirical analysis of multiple objective ant colony optimization algorithms for the bi-criteria TSP | C García-Martínez, O Cordón, F Herrera. | 2004 |
| A study on the evolutionary adaptive defuzzification methods in fuzzy modeling | O Cordón, F Herrera, FA Márquez, A Peregrín. | 2004 |
| Real-coded memetic algorithms with crossover hill-climbing | M Lozano, F Herrera, N Krasnogor, D Molina. | 2004 |
| Special issue on genetic fuzzy systems | O Cordón, FAC Gomide, F Herrera, F Hoffmann, L Magdalena. | 2004 |
| Genetic fuzzy systems. New developments | O Cordón, F Gomide, F Herrera, F Hoffmann, L Magdalena. | 2004 |
| Some issues on consistency of fuzzy preference relations | E Herrera-Viedma, F Herrera, F Chiclana, M Luque. | 2004 |
| Some issues on consistency of fuzzy preference relations. | F Chiclana, F Herrera, E Herrera-Viedma, M Luque. | 2004 |
| Un estudio empırico preliminar sobre los tests estadısticos más habituales en el aprendizaje automático | F Herrera, C Hervás, J Otero, L Sánchez. | 2004 |
| Rationality of induced ordered weighted operators based on the reliability of the source of information in group decision–making | F Chiclana, F Herrera, E Herrera-Viedma. | 2004 |
| Sistemas difusos evolutivos | F Herrera. | 2004 |
| Aprendizaje de Pesos y Selección Evolutiva para la Reducción de la Base de Reglas Difusas | J Alcalá, R Alcalá, O Cordón, F Herrera. | 2004 |
| Genetic fuzzy systems: New developments | O Cordón, F Herrera, F Gomide, F Hoffmann, L Magdalena. | 2004 |
| Linguistic modeling with hierarchical systems of weighted linguistic rules | R Alcalá, JR Cano, O Cordón, F Herrera, P Villar, I Zwir. | 2003 |
| Extracción Evolutiva de Reglas de Asociación en un Servicio de Urgencias Psiquiátricas | JJ Aguilera, MJ Del Jesus, P González, F Herrera, M Navío, J Sáinz. | 2003 |
| A multiobjective genetic learning process for joint feature selection and granularity and contexts learning in fuzzy rule-based classification systems | O Cordón, MJ Del Jesus, F Herrera, L Magdalena, P Villar. | 2003 |
| Using evolutionary algorithms as instance selection for data reduction in KDD: an experimental study | JR Cano, F Herrera, M Lozano. | 2003 |
| Information gathering on the internet using a distributed intelligent agent model with multi-granular linguistic information | F Herrera, E Herrera-Viedma, L Martınez, C Porcel. | 2003 |
| Evaluating the Suitability of an Enterprise Resource Planning System | F Herrera, E Herrera-Viedma, L Martínez, PJ Sánchez. | 2003 |
| A note on the reciprocity in the aggregation of fuzzy preference relations using OWA operators | F Chiclana, F Herrera, E Herrera-Viedma, L Martınez. | 2003 |
| Linguistic modeling with weighted double-consequent fuzzy rules based on cooperative coevolutionary learning | R Alcalá, J Casillas, O Cordón, F Herrera. | 2003 |
| Combining rule weight learning and rule selection to obtain simpler and more accurate linguistic fuzzy models | R Alcalá, O Cordón, F Herrera. | 2003 |
| Preference modeling and applications: EUROFUSE 2001 | B De Baets, M Delgado, J Fodor, F Herrera, E Herrera‐Viedma, .... | 2003 |
| Preference modelling and applications.-Selected papers from EUROFUSE 2001, Granada | B De Baets, M Delgado, F Herrera, E Herrera-Viedma, J Fodor, L Martı́nez. | 2003 |
| Applying rule weight derivation to obtain cooperative rules | R Alcalá, J Casillas, O Cordón, F Herrera. | 2003 |
| An iterative learning methodology to design hierarchical systems of linguistic rules for linguistic modeling | R Alcala, O Cordon, F Herrera, I Zwir. | 2003 |
| Multicriteria Genetic Tuning for the Optimization and Control of HVAC Systems | R Alcala, JM Benitez, J Castillas, JL Castro, O Cordon, A Gonzales, .... | 2003 |
| Interpretability improvements to find the balance interpretability-accuracy in fuzzy modeling: an overview | J Casillas, O Cordon, F Herrera, L Magdalena. | 2003 |
| COR methodology: a simple way to obtain linguistic fuzzy models with good interpretability and accuracy | J Casillas, O Cordón, F Herrera. | 2003 |
| A hierarchical knowledge-based environment for linguistic modeling: models and iterative methodology | O Cordón, F Herrera, I Zwir. | 2003 |
| A taxonomy for the crossover operator for real‐coded genetic algorithms: An experimental study | F Herrera, M Lozano, AM Sánchez. | 2003 |
| Fuzzy adaptive genetic algorithms: design, taxonomy, and future directions | F Herrera, M Lozano. | 2003 |
| A study of the origin and uses of the ordered weighted geometric operator in multicriteria decision making | F Herrera, E Herrera‐Viedma, F Chiclana. | 2003 |
| Interpretability issues in fuzzy modeling. Studies in Fuzziness and Soft Computing. | LM J. Casillas, O. Cordon, F. Herrera. | 2003 |
| Accuracy improvements to find the balance interpretability-accuracy in linguistic fuzzy modeling: an overview | J Casillas, O Cordon, F Herrera, L Magdalena. | 2003 |
| Linguistic preference modeling: foundation models and new trends | F Herrera, E Herrera-Viedma. | 2003 |
| Finding multiple solutions in job shop scheduling by niching genetic algorithms | E Pérez, F Herrera, C Hernández. | 2003 |
| Reciprocity and consistency of fuzzy preference relations | F Chiclana, F Herrera, E Herrera-Viedma. | 2003 |
| A Methodology for Generating the Semantics of Unbalanced Linguistic Term Sets | F Herrera, E Herrera-Viedma, L Martınez, PJ Sánchez. | 2003 |
| Multiple Crossover per Couple with Selection of the Two Best Offspring: An Experimental Study with the BLX-0. Crossover Operator for Real-Coded Genetic Algorithms | F Herrera, M Lozano, E Pérez, AM Sánchez, P Villar. | 2003 |
| Some induced ordered weighting averaging operators to solve decision problems based on fuzzy preference relations | F Chiclana, E Herrera-Viedma, F Herrera. | 2003 |
| Genetic adaption of rule connectives and conjunction operators in fuzzy rule based systems: an experimental comparative study. | F Herrera, FA Márquez, A Peregrín. | 2003 |
| A Linguistic Decision Process for Evaluating the Installation of an Enterprise Resource Planning System | F Herrera, E Herrera-Viedma, L Martınez, PJ Sánchez. | 2003 |
| -Combining Heterogeneous Information in Group Decision Making | F Herrera, E Herrera-Viedma, L Martínez, PJ Sánche. | 2003 |
| Special Issue on Preference Modeling and Applications | B De Baets, M Delgado, F Herrera, E Herrera-Viedma, JC Fodor, .... | 2003 |
| Análisis de distintas vertientes para la paralelización de los algoritmos de Optimización basada en Colonias de Hormigas | S Alonso, O Cordón, IF de Viana, F Herrera. | 2003 |
| Special Issue on Preference Modeling and Applications: EUROFUSE 2001 | B De Baets, M Delgado, J Fodor, F Herrera, E Herrera-Viedma. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Estrategia para la construcción de modelos difusos utilizando clustering y transformación ortogonal | F Herrera, JL Martınez. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| Author's reply [to Comments on'A proposal to improve the accuracy of linguistic modelling'] | O Cordón, F Herrera. | 2003 |
| ¿ Qué ocurre con la adaptación y el rendimiento académico de los alumnos, en un contexto educativo pluricultural? | MI Ramírez, F Herrera, I Herrera. | 2003 |
| A greedy randomized adaptive search procedure applied to the clustering problem as an initialization process using K-Means as a local search procedure | JR Cano, O Cordón, F Herrera, L Sánchez. | 2002 |
| A GRASP algorithm for clustering | JR Cano, O Cordón, F Herrera, L Sánchez. | 2002 |
| Managing heterogeneous information in group decision making | F Herrera, L Martinez, PJ Sanchez, EH Viedma. | 2002 |
| A communication model based on the 2-tuple fuzzy linguistic representation for a distributed intelligent agent system on internet | M Delgado, F Herrera, E Herrera-Viedma, MJ Martín-Bautista, L Martinez, .... | 2002 |
| Representation models for aggregating linguistic information: Issues and analysis | F Herrera, E Herrera-Viedma, L Martinez. | 2002 |
| Fusion of multigranular linguistic information based on the 2-tuple fuzzy linguistic representation model | F Herrera, L Martınez, E Herrera-Viedma, F Chiclana. | 2002 |
| Improving simple linguistic fuzzy models by means of the weighted COR methodology | R Alcalá, J Casillas, O Cordón, F Herrera. | 2002 |
| Hybridizing Hierarchical and Weighted Linguistic Rules | R Alcalá, J Casillas, O Cordón, F Herrera, I Zwir. | 2002 |
| Group Decision Making Based on the Linguistic 2-Tuple Model in Heterogeneous Contexts. | F Herrera, L Martínez-López. | 2002 |
| COR: A methodology to improve ad hoc data-driven linguistic rule learning methods by inducing cooperation among rules | J Casillas, O Cordón, F Herrera. | 2002 |
| Trade-off between accuracy and interpretability in fuzzy rule-based modelling | J Casillas, O Cordon, F Herrera, L Magdalena. | 2002 |
| Different approaches to induce cooperation in fuzzy linguistic models under the COR methodology | J Casillas, O Cordón, F Herrera. | 2002 |
| Linguistic modeling by hierarchical systems of linguistic rules | O Cordón, F Herrera, I Zwir. | 2002 |
| A review on the ant colony optimization metaheuristic: basis, models and new trends | O Cordón, F Herrera, T Stützle. | 2002 |
| Analysis of the best-worst ant system and its variants on the TSP | O Cordón García, I Fernández de Viana, F Herrera Triguero. | 2002 |
| Analysis of the best-worst ant system and its variants on the QAP | O Cordón, IF de Viana, F Herrera. | 2002 |
| An Information Retrieval System with Weighted Querying Based on Multi-Granular Linguistic Information | E Herrera-Viedma, F Herrera, O Cordón, M Luque, AG López. | 2002 |
| Special issue on Ant Colony Optimization | O Cordon, F Herrera, T Stützle. | 2002 |
| A prediction system for cardiovascularity diseases using genetic fuzzy rule-based systems | O Cordón, F Herrera, J de la Montana, AM Sánchez, P Villar. | 2002 |
| Ant colony optimization: models and applications [Guest editorial] | O Cordón García, F Herrera Triguero, T Stützle. | 2002 |
| Guest Editorial: Ant Colony Optimization: Models and Applications | O Cordon, F Herrera, T Stützle. | 2002 |
| A consensus model for multiperson decision making with different preference structures | E Herrera-Viedma, F Herrera, F Chiclana. | 2002 |
| A note on the internal consistency of various preference representations | F Chiclana, F Herrera, E Herrera-Viedma. | 2002 |
| A linguistic decision model for promotion mix management solved with genetic algorithms | F Herrera, E López, MA Rodriguez. | 2002 |
| An information retrieval system with unbalanced linguistic information based on the linguistic 2-tuple model | F Herrera, E Herrera-Viedma, L Martınez. | 2002 |
| Multiple crossover per couple with selection of the two best offspring: an experimental study with the BLX-α crossover operator for real-coded genetic algorithms | F Herrera, M Lozano, E Pérez, AM Sánchez, P Villar. | 2002 |
| Operadores de Cruce con Múltiples Descendientes para Algoritmos Genéticos con Codificación Real: Estudio Experimental | F Herrera, L Manuel, AM Sánchez. | 2002 |
| Techniques for Designing and RefiningLinguistic Fuzzy Models to Improve Their Accuracy | F Herrera, O Cordon, R Alcalá, J Casillas. | 2002 |
| Ant colony optimization: models and applications | O Cordón García, F Herrera, T Stützle. | 2002 |
| Insurance market risk modeling with hierarchical Fuzzy Rule Based Systems | R Alcalá, O Cordón, F Herrera, I Zwir. | 2002 |
| Improvements to the COR Methodology by means of Weighted Fuzzy Rules | R Alcalá, J Casillas, O Cordón, F Herrera. | 2002 |
| Hybridization of Components to Improve the Accuracy in Linguistic Fuzzy Modeling | J Casillas, O Cordón, F Herrera. | 2002 |
| Genetic feature selection in a fuzzy rule-based classification system learning process for high-dimensional problems | J Casillas, O Cordón, MJ Del Jesus, F Herrera. | 2001 |
| A multiobjective genetic algorithm for feature selection and granularity learning in fuzzy-rule based classification systems | O Cordón, F Herrera, MJ Del Jesus, P Villar. | 2001 |
| Feature selection algorithms applied to Parkinson’s disease | M Navío, JJ Aguilera, MJ del Jesús, R González, F Herrera, C Iríbar. | 2001 |
| A model based on linguistic 2-tuples for dealing with multigranular hierarchical linguistic contexts in multi-expert decision-making | F Herrera, L Martínez. | 2001 |
| The 2-tuple linguistic computational model: advantages of its linguistic description, accuracy and consistency | F Herrera, L Martinez. | 2001 |
| A hierarchical ordinal model for managing unbalanced linguistic term sets based on the linguistic 2-tuple model | F Herrera, E Herrera-Viedma, L Martınez. | 2001 |
| Building fuzzy graphs: features and taxonomy of learning for non-grid-oriented fuzzy rule-based systems | R Alcalá, J Casillas, O Cordón, F Herrera. | 2001 |
| La metaheurística de optimización basada en colonias de hormigas: modelos y nuevos enfoques | S Alonso, O Cordón, I Fernández, F Herrera. | 2001 |
| Cooperative coevolution for learning fuzzy rule-based systems | J Casillas, O Cordón, F Herrera, JJ Merelo. | 2001 |
| A multicriteria genetic tuning for fuzzy logic controllers | R Alcalá Fernández, J Casillas Barranquero, JL Castro Peña, .... | 2001 |
| Genetic tuning of fuzzy rule-based systems integrating linguistic hedges | J Casillas, O Cordón, F Herrera, MJ Del Jesus. | 2001 |
| A cooperative coevolutionary algorithm for jointly learning fuzzy rule bases and membership functions. | J Casillas, O Cordón, F Herrera, JJ Merelo. | 2001 |
| Genetic fuzzy systems: evolutionary tuning and learning of fuzzy knowledge bases | O Cordón, F Herrera, F Hoffmann, L Magdalena. | 2001 |
| Generating the knowledge base of a fuzzy rule-based system by the genetic learning of the data base | O Cordón, F Herrera, P Villar. | 2001 |
| Hybridizing genetic algorithms with sharing scheme and evolution strategies for designing approximate fuzzy rule-based systems | O Cordón, F Herrera. | 2001 |
| A genetic learning process for the scaling factors, granularity and contexts of the fuzzy rule-based system data base | O Cordón, F Herrera, L Magdalena, P Villar. | 2001 |
| Fuzzy modeling by hierarchically built fuzzy rule bases | O Cordón, F Herrera, I Zwir. | 2001 |
| Recent advances in genetic fuzzy systems | O Cordón, F Herrera, F Hoffmann, L Magdalena. | 2001 |
| Adaptive genetic operators based on coevolution with fuzzy behaviors | F Herrera, M Lozano. | 2001 |
| Analyzing and extending hierarchical systems of linguistic rules | O Cordon, F Herrera, I Zwir. | 2001 |
| Integrating multiplicative preference relations in a multipurpose decision-making model based on fuzzy preference relations | F Chiclana, F Herrera, E Herrera-Viedma. | 2001 |
| Multiperson decision-making based on multiplicative preference relations | F Herrera, E Herrera-Viedma, F Chiclana. | 2001 |
| Combining linguistic information in a distributed intelligent agent model for information gathering on the Internet | M Delgado, F Herrera, E Herrera-Viedma, MJ Martin-Bautista, MA Vila. | 2001 |
| A linguistic decision model for personnel management solved with a linguistic biobjective genetic algorithm | F Herrera, E López, C Mendaña, MA Rodrı́guez. | 2001 |
| Computing with Words | F Herrera, E Herrera-Viedma. | 2001 |
| Nephrotic syndrome and anasarca status, secondary to treatment with tiopronin in a case of cystinuria]. | NR Alvarez, AP Vidau, SC Rodríguez, PVJ Herrera, HM Suarez. | 2001 |
| Genetic Fuzzy Systems: Evolutionary Tuning and Learning of Fuzzy Knowledge Base | O Gordon, F Herrera, F Hoffmann, M Luis. | 2001 |
| Different proposals to improve the accuracy of fuzzy linguistic modeling | SJIZ O. Cordón, M.J. Del Jesus, F. Herrera. | 2000 |
| A 2-tuple fuzzy linguistic representation model for computing with words | F Herrera, L Martínez. | 2000 |
| A fusion approach for managing multi-granularity linguistic term sets in decision making | F Herrera, E Herrera-Viedma, L Martı́nez. | 2000 |
| An approach for combining linguistic and numerical information based on the 2-tuple fuzzy linguistic representation model in decision-making | F Herrera, L Martinez. | 2000 |
| Learning fuzzy rules using ant colony optimization algorithms | J Casillas, O Cordón, F Herrera. | 2000 |
| Improving the Wang and Mendel’s fuzzy rule learning method by inducing cooperation among rules | J Casillas, O Cordón, F Herrera. | 2000 |
| A methodology to improve ad hoc data-driven linguistic rule learning methods by inducing cooperation among rules | J Casillas, O Cordón, F Herrera. | 2000 |
| Can linguistic modeling be as accurate as fuzzy modeling without losing its description to a high degree | J Casillas, O Cordón, F Herrera. | 2000 |
| Generación de reglas difusas con buen nivel de cooperación mediante algoritmos de hormigas | J Casillas, O Cordón, F Herrera. | 2000 |
| A new ACO model integrating evolutionary computation concepts: The best-worst Ant System | O Cordon, IF de Viana, F Herrera, L Moreno. | 2000 |
| A proposal for improving the accuracy of linguistic modeling | O Cordón, F Herrera. | 2000 |
| Analysis and guidelines to obtain a good uniform fuzzy partition granularity for fuzzy rule-based systems using simulated annealing | O Cordón, F Herrera, P Villar. | 2000 |
| Searching for basic properties obtaining robust implication operators in fuzzy control | O Cordón, F Herrera, A Peregrın. | 2000 |
| Gradual distributed real-coded genetic algorithms | F Herrera, M Lozano. | 2000 |
| Two-loop real-coded genetic algorithms with adaptive control of mutation step sizes | F Herrera, M Lozano. | 2000 |
| Hierarchical knowledge bases for fuzzy rule-based systems | O Cordón, F Herrera, I Zwir. | 2000 |
| Linguistic decision analysis: steps for solving decision problems under linguistic information | F Herrera, E Herrera-Viedma. | 2000 |
| Choice functions and mechanisms for linguistic preference relations | F Herrera, E Herrera-Viedma. | 2000 |
| The ordered weighted geometric operator: properties and application in MCDM Problems | F Chiclana, F Herrera, E Herrera-Viedma. | 2000 |
| A Feedback Process to Model the Consensus in Multiperson Decision Making with Different Preference Representations | E Herrera-Viedma, F Herrera, F Chiclana. | 2000 |
| Adaptive control of the mutation probability by fuzzy logic controllers | F Herrera, M Lozano. | 2000 |
| A proposal on reasoning methods in fuzzy rule-based classification systems | O Cordón, MJ del Jesus, F Herrera. | 1999 |
| Evolutionary approaches to the learning of fuzzy rule-based classification systems | O Cordón, MJ Del Jesus, F Herrera. | 1999 |
| A selection method based on the 2-tuple linguistic representation model for decision-making problems with multi-granularity linguistic information. | F Herrera, L Martínez-López. | 1999 |
| Approximate Mamdani-type fuzzy rule-based systems: Features and taxonomy of learning methods | R Alcalá, J Casillas, O Cordón, F Herrera. | 1999 |
| A two-stage evolutionary process for designing TSK fuzzy rule-based systems | O Cordón, F Herrera. | 1999 |
| Solving electrical distribution problems using hybrid evolutionary data analysis techniques | O Cordón, F Herrera, L Sánchez. | 1999 |
| A practical study on the implementation of fuzzy logic controllers | O Cordón, F Herrera, A Peregrín. | 1999 |
| Hierarchical distributed genetic algorithms | F Herrera, M Lozano, C Moraga. | 1999 |
| Encouraging cooperation in the genetic iterative rule learning approach for qualitative modeling | O Cordón, A Gonzalez, F Herrera, R Perez. | 1999 |
| Looking for the best defuzzification method features for each implication operator to design accurate fuzzy models | O Cordón, F Herrera, A Peregrín. | 1999 |
| ALM: A methodology for designing Accurate Linguistic models for Intelligent Data Analysis | O Cordón, F Herrera. | 1999 |
| MOGUL: A methodology to obtain genetic fuzzy rule-based systems under the iterative rule learning approach | O Cordón, MJ Del Jesus, F Herrera, M Lozano. | 1999 |
| Aggregation of linguistic information based on a symbolic approach | M Delgado, F Herrera, E Herrera-Viedma, JL Verdegay, MA Vila. | 1999 |
| Techniques for learning and tuning fuzzy rule-based systems for linguistic modeling and their application | R Alcalá, J Casillas, O Cordón, F Herrera, I Zwir. | 1999 |
| Solving an assignment–selection problem with verbal information and using genetic algorithms | F Herrera, E López, C Mendaña, MA Rodrı́guez. | 1999 |
| A linguistic decision model to suppliers selection in international purchasing | F Herrera, E López, C Mendaña, MA Rodríguez. | 1999 |
| Solving an Assignment Problem under Linguistic Valuations with Genetic Algorithms | F Herrera, E López, C Mendaña, MA Rodríguez. | 1999 |
| Characterisation of Implication Operators in Fuzzy Rule Based Systems from Basic Properties | O Cordón, F Herrera, A Peregrín. | 1999 |
| ALM: A Methodology for Designing Accurate | O Cordón, F Herrera. | 1999 |
| Genetic learning of fuzzy rule‐based classification systems cooperating with fuzzy reasoning methods | O Cordón, M José del Jesus, F Herrera. | 1998 |
| Analyzing the reasoning mechanisms in fuzzy rule based classification systems | O Cordón, MJ del Jesus, F Herrera. | 1998 |
| Reasoning Methods Based on OWA Operators under Fuzzy Mayority in Fuzzy Rule-Based Classification Systems | O Cordón, MJ Del Jesus, F Herrera, F Herrera. | 1998 |
| Modelado cualitativo utilizando una metodología evolutiva de aprendizaje iterativo de bases de reglas difusas. | O Cordón, MJ del Jesús, F Herrera, M Lozano. | 1998 |
| Combining numerical and linguistic information in group decision making | M Delgado, F Herrera, E Herrera-Viedma, L Martinez. | 1998 |
| Tackling real-coded genetic algorithms: Operators and tools for behavioural analysis | F Herrera, M Lozano, JL Verdegay. | 1998 |
| A learning process for fuzzy control rules using genetic algorithms | F Herrera, M Lozano, JL Verdegay. | 1998 |
| Computing the Spanish medium electrical line maintenance costs by means of evolution-based learning processes | O Cordón, F Herrera, L Sánchez. | 1998 |
| Integrating three representation models in fuzzy multipurpose decision making based on fuzzy preference relations | F Chiclana, F Herrera, E Herrera-Viedma. | 1998 |
| Choice processes for non-homogeneous group decision making in linguistic setting | F Herrera, E Herrera-Viedma, JL Verdegay. | 1998 |
| Integrating Three Representation Models in Fuzzy Multipurpose Decision Making Based on Preference Relations | F Chiclana, E Herrera-Viedma, F Herrera. | 1998 |
| Hybrid distributed real-coded genetic algorithms | F Herrera, M Lozano, C Moraga. | 1998 |
| Choice functions for linguistic preference relations | F Herrera, E Herrera-Viedma. | 1998 |
| Introduction: Genetic fuzzy systems | F Herrera, L Magdalena. | 1998 |
| Adaptive genetic algorithms based on coevolution with fuzzy behaviors | F Herrera, M Lozano. | 1998 |
| Computación Evolutiva. | E Alba, C Cotta, F Herrera. | 1998 |
| Reasoning methods based on OWA operators under fuzzy majority in fuzzy rule-based classification systems | O Cordón, MJ Del Jesus, F Herrera. | 1998 |
| Introduction: Genetic fuzzy systems. | F Herrera, L Magdalena. | 1998 |
| Selecting fuzzy rule-based classification systems with specific reasoning methods using genetic algorithms | O Cordón, MJ del Jesus, F Herrera, E López. | 1997 |
| An evolutionary paradigm for designing fuzzy rule-based systems from examples | O Cordon, MJ del Jesus, F Herrera, M Lozano. | 1997 |
| A three-stage evolutionary process for learning descriptive and approximate fuzzy-logic-controller knowledge bases from examples | O Cordón, F Herrera. | 1997 |
| Applicability of the fuzzy operators in the design of fuzzy logic controllers | O Cordón, F Herrera, A Peregrín. | 1997 |
| On the combination of fuzzy logic and evolutionary computation: a short review and bibliography | O Cordón, F Herrera, M Lozano. | 1997 |
| Fuzzy connectives based crossover operators to model genetic algorithms population diversity | F Herrera, M Lozano, JL Verdegay. | 1997 |
| Identification of Linguistic Fuzzy Models by Means of Genetic Algorithms | O Cordón, F Herrera. | 1997 |
| Evolutionary learning processes for data analysis in electrical engineering applications | O Cordón, F Herrera, L Sánchez. | 1997 |
| Aggregation operators for linguistic weighted information | F Herrera, E Herrera-Viedma. | 1997 |
| A rational consensus model in group decision making using linguistic assessments | F Herrera, E Herrera-Viedma, JL Verdegay. | 1997 |
| Linguistic measures based on fuzzy coincidence for reaching consensus in group decision making | F Herrera, E Herrera-Viedma, JL Verdegay. | 1997 |
| Multi-stage genetic fuzzy systems based on the iterative rule learning approach | A González Muñoz, F Herrera Triguero. | 1997 |
| A classified review on the combination fuzzy logic-genetic algorithms bibliography: 1989-1995 | O Cord6n, F Herrera, M Lozano. | 1997 |
| On the linguistic OWA operator and extensions | F Herrera, E Herrera-Viedma. | 1997 |
| A classified review on the combination fuzzy logic-genetic algorithms bibliography: 1989–1995 | O Cordón, F Herrera, M Lozano. | 1997 |
| Genetic fuzzy systems: A tutorial | F Herrera, L Magdalena. | 1997 |
| Consensus based on fuzzy coincidence for group decision making in linguistic setting | F Herrera, E Herrera-Viedma, JL Verdegay. | 1997 |
| Fuzzy sets and operations research: perspectives | F Herrera, JL Verdegay. | 1997 |
| Ten lectures on genetic fuzzy systems | U Bodenhofer, F Herrera. | 1997 |
| Evolutionary design of TSK fuzzy rule-based systems using (μ, λ)-evolution strategies | O Cordón, F Herrera. | 1997 |
| Heterogeneous distributed genetic algorithms based on the crossover operator | F Herrera, M Lozano. | 1997 |
| Applications of the linguistic OWA operator in group decision making | F Herrera, E Herrera-Viedma, JL Verdegay. | 1997 |
| Special issue on genetic fuzzy systems for control and robotics | F Herrera. | 1997 |
| Gradual distributed genetic algorithms | F Herrera, M Lozano, C Moraga. | 1997 |
| Genetic algorithms and fuzzy logic in control processes | O Cordón, F Herrera, E Herrera-Viedma, M Lozano. | 1996 |
| A three-stage method for designing genetic fuzzy systems by learning from examples | O Cordón, F Herrera, M Lozano. | 1996 |
| A hybrid genetic algorithm-evolution strategy process for learning fuzzy logic controller knowledge bases | O Cordón, F Herrera. | 1996 |
| Dynamic and heuristic fuzzy connectives‐based crossover operators for controlling the diversity and convergence of real‐coded genetic algorithms | F Herrera, M Lozano, JL Verdegay. | 1996 |
| On the bidirectional integration of genetic algorithms and fuzzy logic | O Cordón, F Herrera, M Lozano. | 1996 |
| Generating and selecting fuzzy control rules using evolution strategies and genetic algorithms | O Cordón, F Herrera. | 1996 |
| A model of consensus in group decision making under linguistic assessments | F Herrera, E Herrera-Viedma, JL Verdegay. | 1996 |
| Direct approach processes in group decision making using linguistic OWA operators | F Herrera, E Herrera-Viedma, JL Verdegay. | 1996 |
| A linguistic decision process in group decision making | F Herrera, E Herrera-Viedma, JL Verdegay. | 1996 |
| A classification method of alternatives for multiple preference ordering criteria based on fuzzy majority | F Chiclana, F Herrera, E Herrera-Viedma, MC Poyatos. | 1996 |
| Adaptation of genetic algorithm parameters based on fuzzy logic controllers | F Herrera, M Lozano. | 1996 |
| Genetic algorithms and soft computing | F Herrera, JL Verdegay. | 1996 |
| Preference relations as the information representation base in multi-person decision making | F Chiclana, F Herrera, E Herrera-Viedma. | 1996 |
| Dynamic and heuristic fuzzy connectives-based crossover operators for controlling the diversity and convergence of real-coded genetic algorithms | F Herrera, M Lozano, JL Verdegay. | 1996 |
| Adaptive genetic algorithms based on fuzzy techniques | F Herrera, M Lozano. | 1996 |
| Heuristic crossovers for real-coded genetic algorithms based on fuzzy connectives | F Herrera, M Lozano. | 1996 |
| Fuzzy boolean programming problems with fuzzy costs: A general study | F Herrera, JL Verdegay. | 1996 |
| Making Decisions on Fuzzy Integer Linear Programming Problems | F Herrera, JL Verdegay. | 1996 |
| Generating and selecting fuzzy control rules using evolution strategies and genetic algorithms. In?, editor | O Cordón, F Herrera. | 1996 |
| Evolving neurofuzzy networks for basic behaviors and a recategorization approach for their coordination | M Figueiredo, F Gomide, F Herrera, J Verdegay. | 1996 |
| A general study on genetic fuzzy systems | O Cordón, F Herrera. | 1995 |
| Tuning fuzzy logic controllers by genetic algorithms | F Herrera, M Lozano, JL Verdegay. | 1995 |
| T-norms vs. implication functions as implication operators in fuzzy control | O Cordon, F Herrera, A Peregrin. | 1995 |
| Applicability of T-norms in Fuzzy Control | E Cárdenas, JC Castillo, O Cordón, F Herrera, A Peregrin. | 1995 |
| A sequential selection process in group decision making with a linguistic assessment approach | F Herrera, E Herrera-Viedma, JL Verdegay. | 1995 |
| Generating fuzzy rules from examples using genetic algorithms | F Herrera, M Lozano, JL Verdegay. | 1995 |
| Aggregating linguistic preferences: properties of lowa operator | F Herrera, E Herrera-Viedma, JL Verdegay. | 1995 |
| Three models of fuzzy integer linear programming | F Herrera, JL Verdegay. | 1995 |
| Tackling fuzzy genetic algorithms | F Herrera, M Lozano, JL Verdegay. | 1995 |
| Preference degrees over linguistic preference relations in decision making | F Herrera, E Herrera-Viedma, JL Verdegay. | 1995 |
| Basis for a consensus model in group decision making with linguistic preferences | F Herrera, E Herrera-Viedma, JL Verdegay. | 1995 |
| Design of a control rules base based on genetic algorithms | F Herrera, M Lozano, JL Verdegay. | 1995 |
| Medidas Ling u sticas para el Consenso en Grupo | F Herrera, E Herrera-Viedma, JL Verdegay. | 1995 |
| Algoritmos genéticos: Fundamentos, extensiones y aplicaciones | F Herrera, M Lozano, JL Verdegay. | 1995 |
| Geología del Perú | O Palacios, A Sánchez, F Herrera. | 1995 |
| Geología del Perú. INGEMMET | O Palacios, A Sánchez, F Herrera. | 1995 |
| Influence of fuzzy implication functions and defuzzification methods in fuzzy control | E Cárdenas, JC Castillo, O Cordón, F Herrera, A Peregrín. | 1994 |
| Fuzzy tools to improve genetic algorithms | F Herrera, E Herrera-Viedma, M Lozano, JL Verdegay. | 1994 |
| On dominance degrees in group decision making with linguistic preferences | F Herrera, E Herrera-Viedma, JL Verdegay. | 1994 |
| Applying genetic algorithms in fuzzy optimization problems | F Herrera, M Lozano, JL Verdegay. | 1994 |
| The use of fuzzy connectives to design real-coded genetic algorithms | F Herrera Triguero, M Lozano, JL Verdegay. | 1994 |
| On group decision making under linguistic preferences and fuzzy linguistic quantifiers | F Herrera, JL Verdegay. | 1994 |
| Algoritmos Gen eticos: Fundamentos, Extensiones y Aplicaciones | F Herrera, M Lozano, JL Verdegay. | 1994 |
| Homogeneous linear fuzzy functions and ranking methods in fuzzy linear programming problems | F Herrera, JL Verdegay, M Kovács. | 1994 |
| Knowledge‐based systems and fuzzy boolean programming | JL Castro, F Herrera, JL Verdegay. | 1994 |
| Models and Methods in Fuzzy Discrete Programming | F Herrera. | 1994 |
| The Use of Fuzzy Connectives to Design | F Herrera, M Lozano, JL Verdegay. | 1994 |
| Linguistic assessments in group decision | F Herrera, JL Verdegay. | 1993 |
| Post-optimality analysis on the membership functions of a fuzzy linear programming problem | M Delgado, F Herrera, JL Verdegay, MA Vila. | 1993 |
| A learning method of fuzzy reasoning by genetic algorithms | JL Castro, M Delgado, F Herrera. | 1993 |
| Boolean programming problems with fuzzy constraints | F Herrera, JL Verdegay, HJ Zimmermann. | 1993 |
| Optimality for fuzzified mathematical programming problems: a parametric approach | F Herrera, M Kovacs, JL Verdegay. | 1993 |
| Genetic algorithms applications to fuzzy logic based systems | F Herrera, M Lozano, JL Verdegay. | 1993 |
| Solving linear boolean programming problems with imprecise costs | JL Castro, F Herrera, JL Verdegay. | 1992 |
| An optimum concept for fuzzified linear programming problems: a parametric approach | F Herrera, M Kovács, JL Verdegay. | 1992 |
| Algoritmos Genéticos con Función de Evaluación Difusa y Aplicaciones | JL Castro, M Delgado, F Herrera, JL Verdegay. | 1992 |
| ESTUDIO DE UN SISTEMA INTERACTIVO DE AYUDA A LA DECISION EN PROBLEMAS DE OPTMZACION DIFUSA | JM Cadenas, F Herrera. | 1992 |
| Fuzzy linear programming problems with homogeneous linear fuzzy functions | F Herrera, M Kovacs, JLV López. | 1992 |
| Approaching fuzzy integer linear programming problems | F Herrera, JL Verdegay. | 1991 |
| Problemas y algoritmos de programación entera difusa | F Herrera Triguero. | 1991 |
| On Incompatibility Relations as Models of Potential Conflicts in Knowledge Based Systems | JL Castro, F Herrera. | 1991 |
| Estudio de problemas de Programación Difusa Biobjetivo y su aplicación al Cálculo Proposicional | JL Castro, F Herrera, JL Verdegay. | 1991 |
| Algoritmos y programas:: problemas | JL Castro Peña, F Herrera Triguero, JF Verdegay López. | 1990 |
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