Distance measures of Pythagorean Fuzzy Sets based on sine function in property selection under TOPSIS approach

2022 12th International Conference on Cloud Computing, Data Science & Engineering (Confluence) Pub Date : 2022-01-27 DOI:10.1109/confluence52989.2022.9734130

M. Bhatia, H. Arora, Anjali Naithani, Surbhi Gupta

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引用次数: 1

Abstract

Pythagorean Fuzzy Sets (PFSs) notion which is an extension of Intuitionistic Fuzzy Sets (IFSs), are proven to be highly effective due to its evident flexibility in dealing with an imprecise or uncertain environment. Distance measures between two PFSs are important because they have a range of applications in domains including multicriteria decision making, pattern recognition, and image segmentation. The objective of this study is to introduce trigonometric distance measures for PFSs. Axiomatic properties of distance measures have been proved. Numerical illustration has been offered to ensure the legitimacy and applicability of the proposed measures. The stability and distinctiveness of the proposed measures are applied in a real-life application through a multi-criteria decision-making approach (TOPSIS) which can be applied in diverse situations and simplify the process of decision making. Sensitive analysis has also been carried out to validate proposed measures.

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TOPSIS方法下基于正弦函数的毕达哥拉斯模糊集属性选择的距离度量

毕达哥拉斯模糊集(pfs)概念是直觉模糊集(IFSs)的扩展，由于其在处理不精确或不确定环境中的明显灵活性而被证明是非常有效的。两个pfs之间的距离度量很重要，因为它们在多准则决策、模式识别和图像分割等领域有广泛的应用。本研究的目的是为pfs引入三角距离测量。证明了距离测度的公理化性质。为保证所提措施的合法性和适用性，给出了数值说明。通过一种多准则决策方法(TOPSIS)，将所提出的测量方法的稳定性和独特性应用于实际应用中，该方法可以应用于多种情况并简化决策过程。还进行了敏感分析，以验证所建议的措施。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2022 12th International Conference on Cloud Computing, Data Science & Engineering (Confluence)

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