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Trust recommendation mechanism-based consensus model for Pawlak conflict analysis decision making

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收录情况: ◇ SCIE ◇ EI

机构: [1]School of Economics and Management, Xidian University, Xi’an, 710071, China [2]Department of Big Data Research of Medicine, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, 510120, China [3]The third department of Neurology, the Second Affiliated Hospital of Xi’an Medical University, Xi’an, Shaanxi, China
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关键词: Conflict analysis Consensus reaching process Trust recommendation mechanism Pythagorean fuzzy set

摘要:
Conflict analysis has become a hot issue in management science. In the context of conflict analysis, there are three attitudes for agents to describe the opinion, including supportive, opposite, and neutral. Then, the conflict situation is discussed and analyzed. In this paper, we propose an extended Pawlak conflict model concerning the trust mechanism to solve the problem of the reaching consensus process. Firstly, the degree of conflict is defined by the weights of agents considering the penalty factors, and an extended Pawlak conflict model is presented. Then, the trust recommendation mechanism is proposed to modify the opinions of agents and reach conflict consensus. Four kinds of feedback mechanism are discussed by using four perspectives: 1) without the penalty factors and no limit to the range of adjustments; 2) without the penalty factors and the attitude of agents vary from pessimistic to neutral; 3) with the penalty factors and no limit to the range of adjustments; 4) with the penalty factors and the attitude of agents vary from pessimistic to neutral. Furthermore, this paper presents a process of reaching consensus based on the trust recommendation mechanism for the conflict analysis problem. Finally, a case study is used to validate the effectiveness and superiority of the proposed method. A comparative analysis is completed for the parameters and the maximum alliances could be obtained with the original Pawlak conflict model. (C) 2021 Elsevier Inc. All rights reserved.

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出版当年[2020]版:
大类 | 3 区 工程技术
小类 | 4 区 计算机:人工智能
最新[2025]版:
大类 | 3 区 计算机科学
小类 | 3 区 计算机:人工智能
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出版当年[2019]版:
Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
最新[2023]版:
Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

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第一作者机构: [1]School of Economics and Management, Xidian University, Xi’an, 710071, China
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