| SLAVE: A genetic learning system based on an iterative approach A González, R Pérez Fuzzy Systems, IEEE Transactions on 7 (2), 176-191, 1999 | 361 | 1999 |
| Selection of relevant features in a fuzzy genetic learning algorithm A González, R Pérez IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) 31 …, 2001 | 206 | 2001 |
| Completeness and consistency conditions for learning fuzzy rules A Gonzalez, R Perez Fuzzy Sets and Systems 96 (1), 37-51, 1998 | 191 | 1998 |
| Fuzzy control of HVAC systems optimized by genetic algorithms R Alcalá, JM Benítez, J Casillas, O Cordón, R Pérez Applied Intelligence 18, 155-177, 2003 | 184 | 2003 |
| Three new instance selection methods based on local sets: A comparative study with several approaches from a bi-objective perspective E Leyva, A González, R Pérez Pattern Recognition 48 (4), 1523-1537, 2015 | 126 | 2015 |
| Including a simplicity criterion in the selection of the best rule in a genetic fuzzy learning algorithm L Castillo, A González, R Pérez Fuzzy Sets and Systems 120 (2), 309-321, 2001 | 115 | 2001 |
| A Set of Complexity Measures Designed for Applying Meta-Learning to Instance Selection E Leyva, A González, R Pérez IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 2014 | 96 | 2014 |
| Learning the structure of a fuzzy rule: a genetic approach A González, R Pérez, JL Verdegay Fuzzy Systems and Artificial Intelligence 3 (1), 57-70, 1994 | 76 | 1994 |
| Improving the genetic algorithm of SLAVE A González, R Pérez Mathware & Soft Computing 16 (1), 59-70, 2009 | 57 | 2009 |
| A learning system of fuzzy control rules based on genetic algorithms A Gonzalez, R Perez Genetic algorithms and soft computing, Physica-Verlag, 202-225, 1996 | 44 | 1996 |
| Overview of the SLAVE learning algorithm: A review of its evolution and prospects D García, A González, R Pérez International Journal of Computational Intelligence Systems 7 (6), 1194-1221, 2014 | 39 | 2014 |
| Preface: Special Issue on Genetic Fuzzy Systems and the Interpretability--Accuracy Trade-off J Casillas, F Herrera, R Pérez, MJ del Jesus, P Villar International Journal of Approximate Reasoning 44 (1), 1-3, 2007 | 37 | 2007 |
| A study about the inclusion of linguistic hedges in a fuzzy rule learning algorithm A González, R Pérez International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems …, 1999 | 36 | 1999 |
| Combining instance selection methods based on data characterization: An approach to increase their effectiveness Y Caises, A González, E Leyva, R Pérez Information Sciences 181 (20), 4780-4798, 2011 | 34 | 2011 |
| Knowledge-based instance selection: A compromise between efficiency and versatility E Leyva, A González, R Pérez Knowledge-Based Systems 47, 65-76, 2013 | 31 | 2013 |
| On the use of meta-learning for instance selection: An architecture and an experimental study E Leyva, Y Caises, A González, R Pérez Information Sciences 266, 16-30, 2014 | 23 | 2014 |
| An efficient inductive genetic learning algorithm for fuzzy relational rules A González, R Pérez, Y Caises, E Leyva International Journal of Computational Intelligence Systems 5 (2), 212-230, 2012 | 21 | 2012 |
| Encouraging cooperation in the genetic iterative rule learning approach for qualitative modeling O Cordon, A Gonzalez, F Herrera, R Perez Computing with Words in Information/Intelligent Systems 2: Applications, 95-117, 1999 | 20 | 1999 |
| Learning numerical action models from noisy and partially observable states by means of inductive rule learning techniques JA Segura-Muros, R Pérez, J Fernández-Olivares KEPS 2018 46, 2018 | 18 | 2018 |
| SCIS: combining instance selection methods to increase their effectiveness over a wide range of domains Y Caises, A González, E Leyva, R Pérez Intelligent Data Engineering and Automated Learning-IDEAL 2009: 10th …, 2009 | 17 | 2009 |
Antonio GonzálezProfessor of Computer Science and Artificial Intelligence, Granada UniversityVerified email at decsai.ugr.es
