Interval-valued fuzzy reasoning method by optimizing the similarity of truth-tables

In this paper, we introduce a new interval-valued fuzzy reasoning method by optimizing the similarity of truth- tables(IVOS method for short). The basic idea is to obtain inference results by optimizing the similarity between the truth-table of the antecedent rule and the truth-table of the consequent rule. Firstly, the interval-valued fuzzy implication is constructed according to the fuzzy implication. Secondly, the inference principle of the IVOS method is given. Finally, the IVOS methods using specific similarity and constructed three interval-valued fuzzy implications are investigated.