Fuzzy reasoning method by optimizing the similarity of truth-tables

This paper presents a new fuzzy reasoning method by optimizing the similarity of truth-tables (OS method for short). Its basic idea is to find a fuzzy set such that the truth-tables generated by the antecedent rule and the consequent rule are as similar as possible. Based on this idea, the principle of OS method and the fuzzy reasoning with OS method are given and discussed. And then the OS methods with certain similarity measure and several fuzzy implications are investigated. Finally, numerical examples are analyzed to compare the proposed method with compositional rule of inference (CRI) method.