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

@article{Kung2004ANC,
  title={A new cluster validity criterion for fuzzy c-regression model and its application to T-S fuzzy model identification},
  author={Chung-Chun Kung and Chih-Chien Lin},
  journal={2004 IEEE International Conference on Fuzzy Systems (IEEE Cat. No.04CH37542)},
  year={2004},
  volume={3},
  pages={1673-1678 vol.3}
}
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… CONTINUE READING