Daniel F. Leite
Cited by
Cited by
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
Evolving fuzzy granular modeling from nonstationary fuzzy data streams
D Leite, R Ballini, P Costa, F Gomide
Evolving Systems 3, 65-79, 2012
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
Evolving granular neural networks from fuzzy data streams
D Leite, P Costa, F Gomide
Neural Networks 38, 1-16, 2013
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
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
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
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
An overview on evolving systems and learning from stream data
D Leite, I Škrjanc, F Gomide
Evolving systems 11 (2), 181-198, 2020
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
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
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
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
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
Interval approach for evolving granular system modeling
D Leite, P Costa, F Gomide
Learning in non-stationary environments: methods and applications, 271-300, 2012
Ensemble of evolving optimal granular experts, OWA aggregation, and time series prediction
D Leite, I Škrjanc
Information sciences 504, 95-112, 2019
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
Evolving granular classification neural networks
DF Leite, P Costa, F Gomide
2009 International Joint Conference on Neural Networks, 1736-1743, 2009
Granular approach for evolving system modeling
D Leite, P Costa, F Gomide
Computational Intelligence for Knowledge-Based Systems Design: 13th …, 2010
Evolving neuro-fuzzy network for real-time high impedance fault detection and classification
S Silva, P Costa, M Santana, D Leite
Neural Computing and Applications, 1-14, 2018
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