An Intelligent Expert Combination Weighting Scheme for Group Decision Making in Railway Reconstruction

Lihua Zeng, Haiping Ren, Tonghua Yang and Neal Xiong
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Lihua Zeng: School of Software, Jiangxi University of Science and Technology, Nanchang 330013, China
Haiping Ren: School of Software, Jiangxi University of Science and Technology, Nanchang 330013, China
Tonghua Yang: School of Vocational Education and Technology, Jiangxi Agricultural University, Nanchang 330045, China
Neal Xiong: Department of Mathematics and Computer Science, Northeastern State University, Tahlequah, OK 74133, USA

Mathematics, 2022, vol. 10, issue 4, 1-19

Abstract: The intuitionistic fuzzy entropy has been widely used in measuring the uncertainty of intuitionistic fuzzy sets. In view of some counterintuitive phenomena of the existing intuitionistic fuzzy entropies, this article proposes an improved intuitionistic fuzzy entropy based on the cotangent function, which not only considers the deviation between membership and non-membership, but also expresses the hesitancy degree of decision makers. The analyses and comparison of the data show that the improved entropy is reasonable. Then, a new IF similarity measure whose value is an IF number is proposed. The intuitionistic fuzzy entropy and similarity measure are applied to the study of the expert weight in group decision making. Based on the research of the existing expert clustering and weighting methods, we summarize an intelligent expert combination weighting scheme. Through the new intuitionistic fuzzy similarity, the decision matrix is transformed into a similarity matrix, and through the analysis of threshold change rate and the design of risk parameters, reasonable expert clustering results are obtained. On this basis, each category is weighted; the experts in the category are weighted by entropy weight theory, and the total weight of experts is determined by synthesizing the two weights. This scheme provides a new method in determining the weight of experts objectively and reasonably. Finally, the method is applied to the evaluation of railway reconstruction scheme, and an example shows the feasibility of the method.

Keywords: intuitionistic fuzzy entropy; hesitant degree information; intuitionistic fuzzy group decision making; clustering; intuitionistic fuzzy similarity (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
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