Some New Correlation Coefficient Measures Based on Fermatean Fuzzy Sets using Decision Making Approach in Pattern Analysis and Supplier Selection

IF 1.3 Q3 ENGINEERING, MULTIDISCIPLINARY
Mansi Bhatia, H. Arora, Anjali Naithani
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引用次数: 0

Abstract

Fermatean fuzzy set (FFS) is an effective tool to depict expert reasoning information in the decision‐making process than fuzzy sets (FS), intuitionistic fuzzy sets (IFS), and Pythagorean fuzzy sets (PFS). Keeping in mind the importance of correlation coefficient and application in medical diagnosis, decision making and pattern recognition, several studies on correlation coefficient measures have been proposed in the literature. As there does not exist any study concerning correlation coefficient measures for FFS, in this communication, we propose novel entropy-correlation measures for Fermatean fuzzy sets and applied it decision making problems of pattern analysis and multi-criteria decision making for supplier selection. With the help of proposed correlation coefficient, we establish some weighted measures for FFS. Using numerical computations, we determine the efficacy of the suggested measures over other measures. The aim of this study is to propose a novel and efficient methodology for evaluation of supplier’s selection with uncertain information. Finally, we establish the comparative study of our developed measures over the existing correlation coefficient measures. The analysis showed that the suggested methodology is reliable, flexible, and consistent with the existing techniques.
模式分析和供应商选择中基于Fermatean模糊集的一些新的相关系数测度
与模糊集(FS)、直觉模糊集(IFS)和毕达哥拉斯模糊集(PFS)相比,Fermatean模糊集(FFS)是描述决策过程中专家推理信息的有效工具。考虑到相关系数的重要性及其在医学诊断、决策和模式识别中的应用,文献中提出了一些有关相关系数测度的研究。鉴于目前尚无关于FFS相关系数测度的研究,本文提出了Fermatean模糊集的熵相关测度,并将其应用于模式分析和多准则决策中的供应商选择决策问题。利用提出的相关系数,建立了FFS的加权度量。通过数值计算,我们确定了建议的措施比其他措施的有效性。本研究的目的是提出一种新的、有效的评估不确定信息下供应商选择的方法。最后,对我国开发的相关系数测度与现有相关系数测度进行了比较研究。分析表明,建议的方法是可靠的,灵活的,并与现有技术一致。
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来源期刊
CiteScore
3.80
自引率
6.20%
发文量
57
审稿时长
20 weeks
期刊介绍: IJMEMS is a peer reviewed international journal aiming on both the theoretical and practical aspects of mathematical, engineering and management sciences. The original, not-previously published, research manuscripts on topics such as the following (but not limited to) will be considered for publication: *Mathematical Sciences- applied mathematics and allied fields, operations research, mathematical statistics. *Engineering Sciences- computer science engineering, mechanical engineering, information technology engineering, civil engineering, aeronautical engineering, industrial engineering, systems engineering, reliability engineering, production engineering. *Management Sciences- engineering management, risk management, business models, supply chain management.
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