Robustness of reverse triple I algorithms based on interval-valued fuzzy inference

Abstract

In this paper, the robustness of reverse triple I algorithms based on interval-valued fuzzy inference is discussed. As corollaries of the main results, the sensitivities of interval-valued R -type [ α , β ] -reverse triple I solutions based on three well-known interval-valued residuated implication operators are given. • A new kind of full implication [ α , β ]-reverse triple I algorithm based on interval-valued fuzzy set is proposed. • The R-type [ α , β ]-reverse triple I solutions based on interval-valued fuzzy inference for the both model of IFMP and IFMT are given. • The reverse triple I algorithms based on interval-valued fuzzy set are robust. • The sensitivities of reverse triple I algorithms based on three important interval-valued residuated implications are given. • The robustness of interval-valued reverse triple I algorithms is directly linked to the selection of fuzzy connectives.