| Two-steps learning of Fuzzy Cognitive Maps for prediction and knowledge discovery on the HIV-1 drug resistance G Nápoles, I Grau, R Bello, R Grau Expert Systems with Applications 41 (3), 821-830, 2014 | 107 | 2014 |
| Fuzzy Cognitive Maps Based Models for Pattern Classification: Advances and Challenges G Nápoles Ruiz, ML Espinosa, I Grau, K Vanhoof, R Bello Springer International Publishing, 2017 | 101* | 2017 |
| FCM expert: software tool for scenario analysis and pattern classification based on fuzzy cognitive maps G Nápoles, ML Espinosa, I Grau, K Vanhoof International Journal on Artificial Intelligence Tools 27 (07), 1860010, 2018 | 86 | 2018 |
| Rough cognitive networks G Nápoles, I Grau, E Papageorgiou, R Bello, K Vanhoof Knowledge-Based Systems 91, 46-61, 2016 | 55 | 2016 |
| Fuzzy-rough cognitive networks G Nápoles, C Mosquera, R Falcon, I Grau, R Bello, K Vanhoof Neural Networks 97, 19-27, 2018 | 50 | 2018 |
| Constricted Particle Swarm Optimization based Algorithm for Global Optimization G Nápoles, I Grau, R Bello Polibits 46, 5-11, 2012 | 47 | 2012 |
| SCANERGY: a Scalable and Modular System for Energy Trading Between Prosumers. M Mihaylov, S Jurado, N Avellana, IS Razo-Zapata, K Van Moffaert, ... AAMAS 15, 1917-1918, 2015 | 39 | 2015 |
| Aplicación de sistemas neuroborrosos a problemas de resistencia antiviral del VIH IG García, GN Ruiz, AP Mariño, CM Pérez Revista Cubana de Ciencias Informáticas 6 (2), 1-11, 2012 | 38 | 2012 |
| Modeling implicit bias with fuzzy cognitive maps G Nápoles, I Grau, L Concepción, LK Koumeri, JP Papa Neurocomputing 481, 33-45, 2022 | 37 | 2022 |
| Recurrence-aware long-term cognitive network for explainable pattern classification G Nápoles, Y Salgueiro, I Grau, ML Espinosa IEEE transactions on cybernetics 53 (10), 6083-6094, 2022 | 30 | 2022 |
| Fuzzy cognitive maps tool for scenario analysis and pattern classification G Nápoles, M Leon, I Grau, K Vanhoof 2017 IEEE 29th International Conference on Tools with Artificial …, 2017 | 29 | 2017 |
| A granular intrusion detection system using rough cognitive networks G Nápoles, I Grau, R Falcon, R Bello, K Vanhoof Recent advances in computational intelligence in defense and security, 169-191, 2016 | 26 | 2016 |
| Backpropagation through time algorithm for training recurrent neural networks using variable length instances I Grau, G Nápoles, I Bonet, MM García Computación y Sistemas 17 (1), 15-24, 2013 | 24 | 2013 |
| Modelling, aggregation and simulation of a dynamic biological system through Fuzzy Cognitive Maps G Nápoles, I Grau, M León, R Grau Advances in Computational Intelligence: 11th Mexican International …, 2013 | 23 | 2013 |
| Hybrid model based on rough sets theory and fuzzy cognitive maps for decision-making G Nápoles, I Grau, K Vanhoof, R Bello Rough Sets and Intelligent Systems Paradigms: Second International …, 2014 | 20 | 2014 |
| Fuzzy-rough cognitive networks: Theoretical analysis and simpler models L Concepción, G Nápoles, I Grau, W Pedrycz IEEE Transactions on Cybernetics 52 (5), 2994-3005, 2020 | 18 | 2020 |
| Challenges in describing the conformation and dynamics of proteins with ambiguous behavior J Roca-Martinez, T Lazar, J Gavalda-Garcia, D Bickel, R Pancsa, B Dixit, ... Frontiers in molecular biosciences 9, 959956, 2022 | 17 | 2022 |
| A computational tool for simulation and learning of Fuzzy Cognitive Maps G Nápoles, I Grau, R Bello, M León, K Vahoof, E Papageorgiou 2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 1-8, 2015 | 17 | 2015 |
| Learning of Fuzzy Cognitive Maps for simulation and knowledge discovery G Napoles, I Grau, R Pérez-García, R Bello Fourth International Workshop on Knowledge Discovery, Knowledge Management …, 2013 | 16 | 2013 |
| Recommender system using long-term cognitive networks G Nápoles, I Grau, Y Salgueiro Knowledge-Based Systems 206, 106372, 2020 | 15 | 2020 |
Gonzalo NápolesAssistant Professor at Tilburg University確認したメール アドレス: uvt.nl