On-line fuzzy modeling via clustering and support vector machines

DOI10.1016/j.ins.2008.07.014zbMath1159.68541OpenAlexW2159919201MaRDI QIDQ955239

Xiaoou Li, Wen Yu

Publication date: 19 November 2008

Published in: Information Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ins.2008.07.014

zbMATH Keywords

identificationstabilitysupport vector machinesfuzzy systemson-line clustering

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Related Items (3)

Complex system fault diagnosis based on a fuzzy robust wavelet support vector classifier and an adaptive Gaussian particle swarm optimization ⋮ A hybrid-forecasting model reducing Gaussian noise based on the Gaussian support vector regression machine and chaotic particle swarm optimization ⋮ Air management in a diesel engine using fuzzy control techniques

Uses Software

• ANFIS

Cites Work

• Unnamed Item
• Genetically optimized fuzzy polynomial neural networks with fuzzy set-based polynomial neurons
• A novel feature selection approach: combining feature wrappers and filters
• An approach for fuzzy rule-base adaptation using on-line clustering
• Fuzzy identification of systems and its applications to modeling and control
• Representations of non-linear systems: the NARMAX model

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