Ĩ-Type Interval-Valued Fuzzy Reasoning Method by Optimizing the Similarity of Truth-Tables

In this paper, we further discusses the interval-valued fuzzy reasoning method by optimizing the similarity of truth-tables(IVOS method for short). Firstly, this paper further simplifies the IVOS method by using a particular interval-valued fuzzy implication in order to reduce the computational cost in practical problems. At times, the reasoning ability of the IVOS method, the fully-implicated Triple I method, and the CRI method are compared by using interval-valued fuzzy implication. The experimental results show that the IVOS method has better inference ability, and the IVOS method has stability compared with the full implication triple-I method and the CRI method.