Singular value-based fuzzy rule interpolation

Abstract

In sparse fuzzy rule bases, conventional fuzzy reasoning methods cannot reach a proper conclusion. To eliminate this problem interpolative reasoning has emerged in fuzzy research as a new topic. If the number of variables or the number of fuzzy terms is growing the size of the rule base increases exponentially, hence, the inference/control time also increases considerably. Interpolative reasoning can help to reduce the number of rules, but does not eliminate the problem of exponential growth. Singular value based rule base reduction (FuzzySVD) methods have been published with various conventional methods. This paper introduces the extension of the FuzzySVD method to the specialized fuzzy rule interpolation method to achieve more significant reduction.