Abstract
In this paper, a new cluster validity criterion for fuzzy c-regression models (FCRM) clustering algorithm with affine linear functional cluster representatives is proposed. The proposed cluster validity criterion calculates the overall compactness and separateness of the FCRM partition and then determines the appropriate number of clusters. Besides, its application to fuzzy model identification is discussed. A TS fuzzy model identification algorithm is proposed to extract compact number of IF-THEN rules from data. Two simulation examples are provided to demonstrate the potential of the proposed cluster validity criterion and the accuracy of the constructed T-S fuzzy model.
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