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)

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