| Evolving fuzzy and neuro-fuzzy approaches in clustering, regression, identification, and classification: A survey I Škrjanc, JA Iglesias, A Sanchis, D Leite, E Lughofer, F Gomide Information sciences 490, 344-368, 2019 | 365 | 2019 |
| Evolving fuzzy granular modeling from nonstationary fuzzy data streams D Leite, R Ballini, P Costa, F Gomide Evolving Systems 3 (2), 65-79, 2012 | 155 | 2012 |
| Evolving granular neural networks from fuzzy data streams D Leite, P Costa, F Gomide Neural Networks 38, 1-16, 2013 | 154 | 2013 |
| High impedance fault detection in power distribution systems using wavelet transform and evolving neural network S Silva, P Costa, M Gouvea, A Lacerda, F Alves, D Leite Electric power systems research 154, 474-483, 2018 | 151 | 2018 |
| Ensemble of Evolving Data Clouds and Fuzzy Models for Weather Time Series Prediction E Soares, P Costa, B Costa, D Leite Applied Soft Computing 64, 445–453, 2018 | 131 | 2018 |
| Evolving granular fuzzy model-based control of nonlinear dynamic systems D Leite, R Palhares, V Campos, F Gomide Fuzzy Systems, IEEE Transactions on 23 (4), 923 - 938, 2015 | 121 | 2015 |
| Nonlinear modeling and robust LMI fuzzy control of overhead crane systems C Aguiar, D Leite, D Pereira, G Andonovski, I Škrjanc Journal of the Franklin Institute 358 (2), 1376-1402, 2021 | 93 | 2021 |
| An overview on evolving systems and learning from stream data D Leite, I Škrjanc, F Gomide Evolving systems 11 (2), 181-198, 2020 | 91 | 2020 |
| Real-time anomaly detection in data centers for log-based predictive maintenance using an evolving fuzzy-rule-based approach L Decker, D Leite, L Giommi, D Bonacorsi 2020 IEEE international conference on fuzzy systems (FUZZ-IEEE), 1-8, 2020 | 85 | 2020 |
| Incremental missing-data imputation for evolving fuzzy granular prediction C Garcia, D Leite, I Skrjanc IEEE Transactions on Fuzzy Systems 28 (10), 2348-2362, 2020 | 82 | 2020 |
| Evolving granular neural network for semi-supervised data stream classification D Leite, P Costa, F Gomide The 2010 international joint conference on neural networks (IJCNN), 1-8, 2010 | 79 | 2010 |
| Optimal rule-based granular systems from data streams D Leite, G Andonovski, I Skrjanc, F Gomide IEEE Transactions on Fuzzy Systems 28 (3), 583-596, 2020 | 66 | 2020 |
| Fuzzy clustering and fuzzy validity measures for knowledge discovery and decision making in agricultural engineering VC Mota, FA Damasceno, DF Leite Computers and electronics in agriculture 150, 118-124, 2018 | 55 | 2018 |
| Ensemble of evolving optimal granular experts, OWA aggregation, and time series prediction D Leite, I Škrjanc Information sciences 504, 95-112, 2019 | 54 | 2019 |
| Fuzzy granular evolving modeling for time series prediction D Leite, F Gomide, R Ballini, P Costa 2011 IEEE international conference on fuzzy systems (FUZZ-IEEE 2011), 2794-2801, 2011 | 51 | 2011 |
| Interval approach for evolving granular system modeling D Leite, P Costa, F Gomide Learning in non-stationary environments: methods and applications, 271-300, 2012 | 47 | 2012 |
| Real-time fault diagnosis of nonlinear systems DF Leite, MB Hell, P Costa Jr, F Gomide Nonlinear Analysis: Theory, Methods & Applications 71 (12), e2665-e2673, 2009 | 42 | 2009 |
| Fault detection in smart grids with time-varying distributed generation using wavelet energy and evolving neural networks F Lucas, P Costa, R Batalha, D Leite, I Škrjanc Evolving systems 11 (2), 165-180, 2020 | 39 | 2020 |
| Granular approach for evolving system modeling D Leite, P Costa Jr, F Gomide International Conference on Information Processing and Management of …, 2010 | 38 | 2010 |
| Evolving granular classification neural networks DF Leite, P Costa, F Gomide 2009 International Joint Conference on Neural Networks, 1736-1743, 2009 | 38 | 2009 |
Fernando GomideProfessor of Electrical and Computer Engineering, University of CampinasVerified email at unicamp.br
