Fault diagnosis with evolving fuzzy classifier based on clustering algorithm and drift detection

DOI10.1155/2015/368190zbMath1395.62185OpenAlexW1964550107WikidataQ59118184 ScholiaQ59118184MaRDI QIDQ1665489

Maurilio Inacio, André P. Lemos, Walmir M. Caminhas

Publication date: 27 August 2018

Published in: Mathematical Problems in Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2015/368190

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Multivariate analysis and fuzziness (62H86)

Uses Software

• ElemStatLearn
• DENFIS

Cites Work

• An approach for on-line extraction of fuzzy rules using a self-organising fuzzy neural network
• An approach for fuzzy rule-base adaptation using on-line clustering
• Fault detection for industrial processes
• Sequential adaptive fuzzy inference system (SAFIS) for nonlinear system identification and prediction
• Advances in Artificial Intelligence – SBIA 2004
• The elements of statistical learning. Data mining, inference, and prediction
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