most citedReal-Time Anomaly Detection in Data Centers for Log-based Predictive Maintenance using an Evolving Fuzzy-Rule-Based Approach

3 citations · 4 across the 5 of their papers we have counts for

collaborators

7 papers

cs.LG20211 cited

Adaptive Gaussian Fuzzy Classifier for Real-Time Emotion Recognition in Computer Games

Daniel Leite, Volnei Frigeri, Rodrigo Medeiros

Human emotion recognition has become a need for more realistic and interactive machines and computer systems. The greatest challenge is the availability of high-performance algorit…

eess.SY2021

Evolving Fuzzy System Applied to Battery Charge Capacity Prediction for Fault Prognostics

Murilo Osorio Camargos, Iury Bessa, Luiz A. Q. Cordovil Junior +3

This paper addresses the use of data-driven evolving techniques applied to fault prognostics. In such problems, accurate predictions of multiple steps ahead are essential for the R…

eess.SY2021

Incremental Learning and State-Space Evolving Fuzzy Control of Nonlinear Time-Varying Systems with Unknown Model

Daniel Leite, Pedro Coutinho, Iury Bessa +3

We present a method for incremental modeling and time-varying control of unknown nonlinear systems. The method combines elements of evolving intelligence, granular machine learning…

cs.AI20203 cited

Real-Time Anomaly Detection in Data Centers for Log-based Predictive Maintenance using an Evolving Fuzzy-Rule-Based Approach

Leticia Decker, Daniel Leite, Luca Giommi +1

Detection of anomalous behaviors in data centers is crucial to predictive maintenance and data safety. With data centers, we mean any computer network that allows users to transmit…

cs.AI2020

EGFC: Evolving Gaussian Fuzzy Classifier from Never-Ending Semi-Supervised Data Streams -- With Application to Power Quality Disturbance Detection and Classification

Daniel Leite, Leticia Decker, Marcio Santana +1

Power-quality disturbances lead to several drawbacks such as limitation of the production capacity, increased line and equipment currents, and consequent ohmic losses; higher opera…

cs.NE2020

Comparison of Evolving Granular Classifiers applied to Anomaly Detection for Predictive Maintenance in Computing Centers

Leticia Decker, Daniel Leite, Fabio Viola +1

Log-based predictive maintenance of computing centers is a main concern regarding the worldwide computing grid that supports the CERN (European Organization for Nuclear Research) p…