Research on the problem of aggregation of multiple rules in fuzzy inference systems

Abstract

In this paper, we establish the matching relation between implication operator and aggregation operator, which provides a new solution for the design and construction of multi-rule fuzzy inference system. Firstly, according to the definition and monotonicity of implication operator, a new classification method of implication operator is proposed, and then the fuzzy inference process using different implication operators is classified. Then, dynamic maximum aggregation operator and dynamic minimum aggregation operator are proposed. Based on the compositional rule of inference (CRI) method, a matching method and basis of implication operator and aggregation operator for fuzzy inference systems is given and illustrated with examples. Finally, the applicability of the proposed method in this paper is further illustrated by comparing the method with existing methods in the literature and using the nearness degree as an evaluation index.