Effectiveness of Logarithmic Entropy Measures for Pythagorean Fuzzy Sets in diseases related to Post COVID Implications under TOPSIS Approach

Q3 Computer Science International Journal of Intelligent Systems and Applications in Engineering Pub Date : 2021-12-26 DOI:10.18201/ijisae.2021473637

Yazar Adı Yazar Soyadı, Anjali Naithani

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引用次数: 3

Abstract

Following the second wave of Covid-19 infections in India, individuals are now arriving to hospitals with a variety of symptoms, not simply for mucormycosis, a fungal infection. The most common symptoms are extreme tiredness, drowsiness, body and joint pain, mental fog, and fever, but pneumonia, collapsed lungs, heart attacks, and strokes have all been reported. Pythagorean fuzzy sets (PFSs) proposed by Yager [42] offers a novel technique to characterize uncertainty and ambiguity with greater precision and accuracy. The idea was developed specifically to describe uncertainty and ambiguity mathematically and to provide a codified tool for dealing with imprecision in real-world circumstances. This article addresses novel logarithmic entropy measures under PFSs. Additionally, numerical illustration is utilized to ascertain the strength and validity of the proposed entropy measures. Application of the measures is used in detecting diseases related to Post COVID 19 implications through TOPSIS method. Comparison of the suggested measures with the existing ones is also demonstrated. © 2021, Ismail Saritas. All rights reserved.

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TOPSIS方法下勾股模糊集的对数熵测度在新冠肺炎后相关疾病中的有效性

在印度发生第二波新冠肺炎感染后，人们带着各种症状来到医院，而不仅仅是因为毛霉菌病，一种真菌感染。最常见的症状是极度疲劳、嗜睡、身体和关节疼痛、精神迷雾和发烧，但肺炎、肺部塌陷、心脏病发作和中风都有报道。Yager[42]提出的勾股模糊集（PFSs）提供了一种新的技术来更精确地刻画不确定性和模糊性。这个想法是专门为在数学上描述不确定性和模糊性而开发的，并为处理现实世界环境中的不精确性提供了一个编码工具。本文讨论了PFSs下新的对数熵度量。此外，还利用数值说明来确定所提出的熵度量的强度和有效性。这些措施的应用用于通过TOPSIS方法检测与2019冠状病毒病后影响相关的疾病。还展示了所建议的措施与现有措施的比较。©2021，伊斯梅尔·萨里塔斯。保留所有权利。

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