犹豫模糊图的余弦相似度度量及其在决策中的应用

IF 1.8 3区 数学 Q1 MATHEMATICS
Rajagopal Reddy N, S. Basha. S
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引用次数: 1

摘要

通过实例验证,提出了一种新的犹豫模糊图间余弦相似度度量方法,该方法在群体决策问题中具有比现有模糊图更强的判别能力。本研究提出了一种估算专家认证声誉分数的新方法,该方法通过确定一个可分离的犹豫模糊偏好关系的模糊信息以及一个可分离的犹豫模糊偏好关系与其他一些可分离的犹豫模糊偏好关系的规则余弦相似度来估计专家认证声誉分数。这种新方法同时考虑了专家提供的“客观”和“主观”信息。运用犹豫模糊偏好关系,构建了评估专家信誉分数的工作程序。在考虑多个相互冲突的因素的评估中,这可以应用于增加或减少指定标准的相关性。应用新提出的余弦相似度度量和犹豫模糊图能量这两种有效的方法,给出了一个决策问题的解。最后,给出了两种工作流程和实例,验证了所提技术的实用性和优势性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A cosine similarity measures between hesitancy fuzzy graphs and its application to decision making
A new cosine similarity measure between hesitancy fuzzy graphs, which have been shown to have greater discriminating capacity than certain current ones in group decision making problems by example verification. This study proposes a novel method for estimating expert-certified repute scores by determining the ambiguous information of hesitancy fuzzy preference relations as well as the regular cosine similarity grades from one separable hesitancy fuzzy preference relation to some others. The new approach considers both "objective" and "subjective" information given by experts. We construct working procedures for assessing the eligible reputational scores of the experts by applying hesitancy fuzzy preference relations. In an evaluation in which multiple conflicting factors are taken into consideration, this can be applied to increase or reduce the relevancy of specified criteria. Applying the two effective methods, the newly developed cosine similarity measure, the energy of hesitancy fuzzy graph, and we provide a solution to a decisional issue. Finally, the two working procedures and examples are given to verify the practicality and dominance of the proposed techniques.
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来源期刊
AIMS Mathematics
AIMS Mathematics Mathematics-General Mathematics
CiteScore
3.40
自引率
13.60%
发文量
769
审稿时长
90 days
期刊介绍: AIMS Mathematics is an international Open Access journal devoted to publishing peer-reviewed, high quality, original papers in all fields of mathematics. We publish the following article types: original research articles, reviews, editorials, letters, and conference reports.
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