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Article type: Research Article
Authors: Liu, Donghai; * | Luo, Yan
Affiliations: Department of Statistics, Hunan University ofScience and Technology, Xiangtan, Hunan, P.R. China
Correspondence: [*] Corresponding author. Donghai Liu, Department of Statistics, Hunan University of Science and Technology, Xiangtan, Hunan 411201, P.R. China. E-mail: [email protected].
Abstract: Although some correlation measure of intuitionistic fuzzy sets(IFSs) have been proposed, some of them cannot express the consistency of information or satisfy the axioms of similarity measure. In this paper, we present a consensus reaching process based on the concordance correlation measure of IFSs in multi-criteria decision making problems. Firstly, we define an innovative concordance correlation measure of IFSs, which not only takes the average information deviation of IFSs into account but also overcomes the disadvantages of previous correlation measures. In addition, its properties and the relationship between the defined new concordance correlation measure and Pearson correlation coefficient of IFSs are discussed. Secondly, considering that the classical TOPSIS method cannot be applied to the correlation measure with negative values, we continue to introduce the concept of relative concordance correlation measure and propose a consensus reaching process with minimum adjustment for an innovative behavioral TOPSIS method. Furthermore, a detailed numerical example and the comparison analyses are provided to verify the advantages of the proposed method. At last, we discuss the sensitivity and stability of the method.
Keywords: Concordance correlation measure, Consensus reaching process, Intuitionistic fuzy set, Behavioral TOPSIS
DOI: 10.3233/JIFS-210343
Journal: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 2, pp. 3121-3136, 2021
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