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

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2 Author(s)
Chung-Chun Kung ; Dept. of Electr. Eng., Tatung Univ., Taipei, Taiwan ; Chih-Chien Lin

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.

Published in:

Fuzzy Systems, 2004. Proceedings. 2004 IEEE International Conference on  (Volume:3 )

Date of Conference:

25-29 July 2004