Computer Engineering Commons^™

Extracting Fuzzy Sparse Rule Base By Cartesian Representation And Clustering, Yeung Yam, Vladik Kreinovich, Hung T. Nguyen

Departmental Technical Reports (CS)

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.