FUZZY INTERPOLATIVE REASONING METHODS AND ALGORITHMS FOR THE SPARSE FUZZY RULE

摘要

In this paper, a new fuzzy interpolative reasoning method is proposed for the sparse rule bases by using the highest points and slopes of the antecedent and consequent fuzzy sets. The proposed fuzzy reasoning methods are not only suitable for the four kinds of fuzzy sets in inference rules, but also can guarantee the convexity and normality of the reasoning consequence. Furthermore, the computation is simpler than the existing fuzzy interpolative reasoning methods.