Extracting Fuzzy Sparse Rule Base by Cartesian Representation and Clustering

Authors

Yeung Yam
Vladik Kreinovich, The University of Texas at El PasoFollow
Hung T. Nguyen

Publication Date

7-2000

Comments

UTEP-CS-00-29.

Published in Proceedings of the 2000 IEEE Conference on Systems, Man, and Cybernetics SMC'2000, Nashville, TN, October 8-10, pp. 2778-2783.

Abstract

Sparse rule base and interpolation have been proposed as possible solution to alleviate the geometric complexity problem of large fuzzy set. However, no formal method to extract sparse rule base is yet available. This paper combines the recently introduced Cartesian representation of membership functions and a mountain method-based clustering technique for extraction. A case study is included to demonstrate the effectiveness of the approach.