Relevance of Polynomial Order in Takagi-Sugeno Fuzzy Inference Systems Applied in Diagnosis Problems

Abstract

Nowadays Takagi Sugeno Fuzzy Inference Systems provide an interesting alternative to solve different kind of problems, and this is because this approach offers versatility and easy design. One of the applications of this kind of Fuzzy Inference Systems is in the classification area, specifically in diagnosis problems, in order to be used as computer aided systems, and this provides interesting results. This paper aims at evaluating the performance of this kind of systems in diagnosis problems, but modifying the order of the Sugeno polynomial. This polynomial is originally a first-order polynomial that relates the inputs with the firing force of the rules. However, with the emergence of high-order Sugeno polynomials is interesting to evaluate how this approach can improve the performance of the Takagi Sugeno Fuzzy Inference Systems. On the other hand, we evaluate the performance by changing the order of the Sugeno polynomial for Type-1, Interval Type-2 and General Type-2 Fuzzy Inference Systems, in order to obtain a tendency of the performance with respect to the order of the Sugeno polynomial.