基于毕达哥拉斯模糊集的最小调整视觉社会网络群体共识方法

IF 1.9 4区 数学 Q1 MATHEMATICS Iranian Journal of Fuzzy Systems Pub Date : 2021-12-01 DOI:10.22111/IJFS.2021.6340
Y. Liu, W. Diao, J. Yang, J. Yi
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引用次数: 0

摘要

人们对意见表达决策空间的要求越来越高,确定当前共识阈值的方法仍然难以捉摸。为了处理海量多样的用户信息,深入探讨社交网络中的阈值问题,建立了一种具有新的偏好结构的一致性模型。本文将毕达哥拉斯模糊数(pfn)引入社会网络群体决策中,分别用于表达决策者的偏好,定义距离度量、共识指数和阈值无差异曲线的概念。此外,通过确定达成共识前阈值的设置规则,建立了最小调整的毕达哥拉斯模糊群体共识模型。最后,利用该模型求解方舱医院的选择问题。
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A visual social network group consensus approach with minimum adjustment based on Pythagorean fuzzy set
People's demand for the decision-making space of opinion expression is getting higher, and the methods to determine the threshold value of current consensus still remain elusive. To deal with large and diverse information of users and discuss deeply the threshold in social networks, we establish a new consistency model with a new preference structure. In this paper, the Pythagorean fuzzy numbers (PFNs) are introduced into social network group decision-making for the expression of decision-makers' preference (DMs) and the concepts definition of the distance measurements, consensus index, and threshold indifference curves, respectively. In addition, we establish a Pythagorean fuzzy group consensus model with minimum adjustment through determining the setting rule of threshold value before reaching the consensus. Finally, we use the proposed model to solve the selection of square cabin hospitals.
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来源期刊
CiteScore
3.50
自引率
16.70%
发文量
0
期刊介绍: The two-monthly Iranian Journal of Fuzzy Systems (IJFS) aims to provide an international forum for refereed original research works in the theory and applications of fuzzy sets and systems in the areas of foundations, pure mathematics, artificial intelligence, control, robotics, data analysis, data mining, decision making, finance and management, information systems, operations research, pattern recognition and image processing, soft computing and uncertainty modeling. Manuscripts submitted to the IJFS must be original unpublished work and should not be in consideration for publication elsewhere.
期刊最新文献
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