A new cluster validity criterion for fuzzy c-regression model and its application to T-S fuzzy model identification

Chung-Chun Kung Chung-Chun Kung,Chih-Chien Lin Chih-Chien Lin

doi:10.1109/fuzzy.2004.1375432

A new cluster validity criterion for fuzzy c-regression model and its application to T-S fuzzy model identification

Chung-Chun Kung Chung-Chun Kung, Chih-Chien Lin Chih-Chien Lin

https://doi.org/10.1109/fuzzy.2004.1375432

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Publication Date: Jul 25, 2004

Citations: 13

Affiliation: Tatung University

#Fuzzy C-regression Model #Cluster Validity Criterion + Show 8 more

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Abstract

This paper proposes a new cluster validity criterion designed for the fuzzy c-regression model (FCRM) clustering algorithm. The proposed cluster validity criterion is utilized to determine the appropriate number of clusters in the FCRM. A systematic procedure for the T-S fuzzy model identification is proposed based on the FCRM accompanied with the new cluster validity criterion. Simulation results show that for a given nonlinear system, the proposed algorithm can effectively and accurately obtain a T-S fuzzy model for it.

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