Target Damage Assessment Method Based on Interval‐Valued Intuitionistic Fuzzy Aggregation Operator under Dynamic Multi‐Expert

Abstract

This study aims to solve the problem that the current target damage assessment method does not fully take into account the time series characteristics of the target and the dynamic changes in the battlefield situation, thus leading to insufficient accuracy of the assessment results. Target damage assessment method based on interval‐valued intuitionistic fuzzy aggregation operator (IVIFAO) under dynamic multi‐experts is a combination of interval‐valued intuitionistic fuzzy set (IVIFS) theory and dynamic multi‐attribute swarm decision‐making theory. Firstly, we extracted the effective factors that cause damage to the target and established the damage assessment index system. Secondly, in order to take into account the subjective weights and objective weights, we proposed a comprehensive weight model of damage factors based on interval‐valued intuitionistic fuzzy entropy (IVIFE) based on a cosine function (IVIFECF). The spatio‐temporal weights for each moment are determined using the Poisson distribution method. Then, given the inherent ambiguity and complexity of the decision‐making process, the decision‐making information is represented by interval‐valued intuitionistic fuzzy numbers (IVIFNs). We constructed a weighted interval‐valued intuitionistic fuzzy (WIVIF) decision matrix. Here, the interval‐valued intuitionistic fuzzy weighted geometric average (IVIFPWGA) operator is used to synthesize decision‐making information related to damage factors. We further introduce the dynamic interval‐valued intuitionistic fuzzy power‐weighted geometric average (DIVIFPWGA) operator, which combines instantaneous decision information with time series weights to generate a dynamic multi‐expert fusion WIVIF decision matrix. Finally, the improved TOPSIS method is used to rank the IVIFNs, resulting in a comprehensive damage assessment of the targets, which is analysed for superiority with the novel method, comparing both real‐time and scalability. The stability and validity of the method were verified.