Linguistic truth-valued intuitionistic fuzzy reasoning with applications in human factors engineering
It is useful to process information expressed by linguistic terms under uncertain environment. This paper proposes a layered reasoning algorithm of the linguistic truth-valued intuitionistic fuzzy lattice. Based on linguistic truth-valued intuitionistic fuzzy algebra (LTV-IFA), some concepts and properties of a new intuitionistic fuzzy layered aggregation (IFLA) operator and its inverse operator are discussed. By using IFLA operators, we present two types of implication operators and a LTV-IFA-based reasoning algorithm. The proposed method can express not only positive evidence, negative evidence and indeterminacy at the same time, but both comparable and incomparable information as well. We carried out a case study based on 10 LTV-IFA, where a human factors engineering analysis in the area of safety management of marine engineering is considered. Comparative results using two implication operations demonstrate that the proposed reasoning approach performs better.
linguistic truth-valued intuitionistic fuzzy reasoning human factors engineering intuitionistic fuzzy layered aggregation operator