Evolving granular classification neural networks. - Daniel F. Leite; Pyramo Costa Jr.; Fernando A. C. Gomide (IJCNN, 2009)

Evolving granular neural network for semi-supervised data stream classification. - Daniel F. Leite; Pyramo Costa Jr.; Fernando A. C. Gomide (IJCNN, 2010)

Granular Approach for Evolving System Modeling. - Daniel F. Leite; Pyramo Costa Jr.; Fernando A. C. Gomide (IPMU, 2010)

Fuzzy granular evolving modeling for time series prediction. - Daniel F. Leite; Fernando A. C. Gomide; Rosangela Ballini; Pyramo Costa Jr. (FUZZ-IEEE, 2011)

Evolving fuzzy linear regression tree approach for forecasting sales volume of petroleum products. - André Paim Lemos; Daniel F. Leite; Leandro Maciel; Rosangela Ballini; Walmir M. Caminhas; Fernando A. C. Gomide (FUZZ-IEEE, 2012)

Evolving granular neural network for fuzzy time series forecasting. - Daniel F. Leite; Pyramo Costa Jr.; Fernando A. C. Gomide (IJCNN, 2012)

Evolving fuzzy granular modeling from nonstationary fuzzy data streams. - Daniel F. Leite; Rosangela Ballini; Pyramo Costa Jr.; Fernando A. C. Gomide (Evol. Syst., 2012)

Sistemas granulares evolutivos. - Daniel Furtado Leite (2012)

Evolving Linguistic Fuzzy Models from Data Streams. - Daniel F. Leite; Fernando A. C. Gomide (Combining Experimentation and Theory, 2012)

Evolving granular neural networks from fuzzy data streams. - Daniel F. Leite; Pyramo Costa Jr.; Fernando A. C. Gomide (Neural Networks, 2013)

Evolving ensemble of fuzzy models for multivariate time series prediction. - Lourenco Bueno; Pyramo Costa; Israel Mendes; Enderson Cruz; Daniel F. Leite (FUZZ-IEEE, 2015)

Evolving Granular Fuzzy Model-Based Control of Nonlinear Dynamic Systems. - Daniel F. Leite; Reinaldo M. Palhares; Víctor C. S. Campos; Fernando A. C. Gomide (IEEE Trans. Fuzzy Syst., 2015)

Incremental Granular Fuzzy Modeling Using Imprecise Data Streams. - Daniel F. Leite; Fernando A. C. Gomide (Fifty Years of Fuzzy Logic and its Applications, 2015)

Fuzzy Granular Neural Network for incremental modeling of nonlinear chaotic systems. - Daniel F. Leite; Marcio Santana; Ana Borges; Fernando A. C. Gomide (FUZZ-IEEE, 2016)

Fuzzy clustering methods applied to the evaluation of compost bedded pack barns. - Vania C. Mota; Flavio A. Damasceno; Eduardo A. Soares 001; Daniel F. Leite (FUZZ-IEEE, 2017)

Cloud-based evolving intelligent method for weather time series prediction. - Eduardo A. Soares 001; Vania C. Mota; Ricardo Poucas; Daniel F. Leite (FUZZ-IEEE, 2017)

Incremental Gaussian Granular Fuzzy Modeling Applied to Hurricane Track Forecasting. - Eduardo A. Soares 001; Heloisa A. Camargo; Suzana J. Camargo; Daniel F. Leite (FUZZ-IEEE, 2018)

High Impedance Fault Detection in Time-Varying Distributed Generation Systems Using Adaptive Neural Networks. - Fabricio P. Lucas; Pyramo Costa; Rose M. S. Batalha; Daniel F. Leite (IJCNN, 2018)

Ensemble of evolving data clouds and fuzzy models for weather time series prediction. - Eduardo A. Soares 001; Pyramo Costa; Bruno Costa 004; Daniel F. Leite (Appl. Soft Comput., 2018)

Fuzzy clustering and fuzzy validity measures for knowledge discovery and decision making in agricultural engineering. - Vania C. Mota; Flavio A. Damasceno; Daniel F. Leite (Comput. Electron. Agric., 2018)

Nonlinear Fuzzy State-Space Modeling and LMI Fuzzy Control of Overhead Cranes. - Daniel F. Leite; Charles Aguiar; Daniel Pereira; Gustavo Souza; Igor Skrjanc (FUZZ-IEEE, 2019)

Multiobjective Optimization of Fully Autonomous Evolving Fuzzy Granular Models. - Daniel F. Leite; Fernando A. C. Gomide; Igor Skrjanc (FUZZ-IEEE, 2019)

Ensemble of evolving optimal granular experts, OWA aggregation, and time series prediction. - Daniel F. Leite; Igor Skrjanc (Inf. Sci., 2019)

Evolving fuzzy and neuro-fuzzy approaches in clustering, regression, identification, and classification: A Survey. - Igor Skrjanc; José Antonio Iglesias 001; Araceli Sanchis; Daniel F. Leite; Edwin Lughofer; Fernando A. C. Gomide (Inf. Sci., 2019)

Evolvable fuzzy systems from data streams with missing values: With application to temporal pattern recognition and cryptocurrency prediction. - Cristiano Garcia; Ahmed Esmin; Daniel F. Leite; Igor Skrjanc (Pattern Recognit. Lett., 2019)

Unsupervised Fuzzy eIX: Evolving Internal-eXternal Fuzzy Clustering. - Charles Aguiar; Daniel F. Leite (EAIS, 2020)

Comparison of Evolving Granular Classifiers applied to Anomaly Detection for Predictive Maintenance in Computing Centers. - Leticia Decker; Daniel F. Leite; Fabio Viola; Daniele Bonacorsi (EAIS, 2020)

Real-Time Anomaly Detection in Data Centers for Log-based Predictive Maintenance using an Evolving Fuzzy-Rule-Based Approach. - Leticia Decker; Daniel F. Leite; Luca Giommi; Daniele Bonacorsi (FUZZ-IEEE, 2020)

EGFC: Evolving Gaussian Fuzzy Classifier from Never-Ending Semi-Supervised Data Streams - With Application to Power Quality Disturbance Detection and Classification. - Daniel F. Leite; Leticia Decker; Marcio Santana; Paulo Vitor de Campos Souza (FUZZ-IEEE, 2020)

An overview on evolving systems and learning from stream data. - Daniel F. Leite; Igor Skrjanc; Fernando A. C. Gomide (Evol. Syst., 2020)

Fault detection in smart grids with time-varying distributed generation using wavelet energy and evolving neural networks. - Fabricio P. Lucas; Pyramo Costa; Rose M. S. Batalha; Daniel F. Leite; Igor Skrjanc (Evol. Syst., 2020)

Evolving neuro-fuzzy network for real-time high impedance fault detection and classification. - Sergio Silva; Pyramo Costa; Marcio Santana; Daniel F. Leite (Neural Comput. Appl., 2020)

Incremental Missing-Data Imputation for Evolving Fuzzy Granular Prediction. - Cristiano Garcia; Daniel F. Leite; Igor Skrjanc (IEEE Trans. Fuzzy Syst., 2020)

Optimal Rule-Based Granular Systems From Data Streams. - Daniel F. Leite; Goran Andonovski; Igor Skrjanc; Fernando A. C. Gomide (IEEE Trans. Fuzzy Syst., 2020)

Incremental Learning and State-Space Evolving Fuzzy Control of Nonlinear Time-Varying Systems with Unknown Model. - Daniel Leite 001; Pedro Henrique Silva Coutinho; Iury Bessa; Murilo C. O. Camargos; Luiz A. Q. Cordovil Júnior; Reinaldo M. Palhares (IFSA/EUSFLAT/AGOP, 2021)

Evolving Fuzzy System Applied to Battery Charge Capacity Prediction for Fault Prognostics. - Murilo C. O. Camargos; Iury Bessa; Luiz A. Q. Cordovil Júnior; Pedro Henrique Silva Coutinho; Daniel Furtado Leite; Reinaldo Martinez Palhares (IFSA/EUSFLAT/AGOP, 2021)

Adaptive Gaussian Fuzzy Classifier for Real-Time Emotion Recognition in Computer Games. - Daniel F. Leite; Volnei Frigeri Jr.; Rodrigo Medeiros (LA-CCI, 2021)

Nonlinear modeling and robust LMI fuzzy control of overhead crane systems. - Charles Aguiar; Daniel F. Leite; Daniel Pereira; Goran Andonovski; Igor Skrjanc (J. Frankl. Inst., 2021)

Explainable Log Parsing and Online Interval Granular Classification from Streams of Words. - Leticia Decker; Daniel F. Leite; Daniele Bonacorsi (FUZZ-IEEE, 2022)

Data Driven Fuzzy Modeling Using Level Sets. - Daniel F. Leite; Fernando A. C. Gomide; Ronald R. Yager (FUZZ-IEEE, 2022)

Fuzzy Linguistic Summaries for Explaining Online Semi-Supervised Learning. - Katarzyna Kaczmarek-Majer; Gabriella Casalino; Giovanna Castellano; Daniel F. Leite; Olgierd Hryniewicz (IS, 2022)

Ensemble of hybrid Bayesian networks for predicting the AMEn of broiler feedstuffs. - Tatiane Carvalho Alvarenga; Renato Ribeiro de Lima; Sérgio Domingos Simão; Luiz Carlos Brandão Júnior; Júlio Sílvio de Sousa Bueno Filho; Renata Ribeiro Alvarenga; Paulo Borges Rodrigues; Daniel Furtado Leite (Comput. Electron. Agric., 2022)

Unsupervised Learning and Online Anomaly Detection: An On-Condition Log-Based Maintenance System. - Leticia Decker; Daniel F. Leite; Francesco Minarini; Simone Rossi Tisbeni; Daniele Bonacorsi (Int. J. Embed. Real Time Commun. Syst., 2022)

Data Driven Fuzzy and Neural Dynamic Systems Modeling. - Daniel F. Leite; Fernando A. C. Gomide (ICMLC, 2023)

Semi-supervised vs. supervised learning for mental health monitoring: A case study on bipolar disorder. - Gabriella Casalino; Giovanna Castellano; Olgierd Hryniewicz; Daniel Leite 001; Karol R. Opara; Weronika Radziszewska; Katarzyna Kaczmarek-Majer (Int. J. Appl. Math. Comput. Sci., 2023)

Interval incremental learning of interval data streams and application to vehicle tracking. - Daniel F. Leite; Igor Skrjanc; Saso Blazic; Andrej Zdesar; Fernando A. C. Gomide (Inf. Sci., 2023)

Obituary Edwin Lughofer (1972-2023). - Plamen Angelov 001; Dimitar P. Filev; Nikola K. Kasabov; Daniel Leite 001; Maharadhika Pratama; Susanne Saminger-Platz; Erich-Peter Klement (Evol. Syst., 2023)

EGNN-C+: Interpretable Evolving Granular Neural Network and Application in Classification of Weakly-Supervised EEG Data Streams. - Daniel F. Leite; Alisson Silva; Gabriella Casalino; Arnab Sharma; Danielle Fortunato; Axel-Cyrille Ngonga Ngomo (EAIS, 2024)

Interpretability Index Based on Balanced Volumes for Transparent Models and Agnostic Explainers. - Daniel F. Leite; Arnab Sharma; Caglar Demir; Axel-Cyrille Ngonga Ngomo (FUZZ, 2024)

Trading-Off Interpretability and Accuracy in Medical Applications: A Study Toward Optimal Explainability of Hoeffding Trees. - Arnab Sharma; Daniel F. Leite; Caglar Demir; Axel-Cyrille Ngonga Ngomo (FUZZ, 2024)

From Model-Based and Adaptive Control to Evolving Fuzzy Control. - Daniel F. Leite; Igor Skrjanc; Fernando A. C. Gomide (CoRR, 2025)