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

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Název: Effectiveness of Logarithmic Entropy Measures for Pythagorean Fuzzy Sets in diseases related to Post COVID Implications under TOPSIS Approach
Autoři: Arora, Hari Darshan, Naithani, Anjali
Zdroj: International Journal of Intelligent Systems and Applications in Engineering; Vol. 9 No. 4 (2021); 178-183
Informace o vydavateli: International Journal of Intelligent Systems and Applications in Engineering, 2021.
Rok vydání: 2021
Témata: Decision making, Entropy measure, Intuitionistic fuzzy set, Logarithmic function, Pythagorean fuzzy sets, Weighted entropy measures, Fuzzy Sets, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, Intelligent Systems, 3. Good health
Popis: 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 [40] 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. 
Druh dokumentu: Article
Popis souboru: application/pdf
Jazyk: English
ISSN: 2147-6799
DOI: 10.18201/ijisae.2021473637
Přístupová URL adresa: https://ijisae.org/index.php/IJISAE/article/download/1268/660/5285
https://www.ijisae.org/index.php/IJISAE/article/view/1268
Přístupové číslo: edsair.doi.dedup.....f3cf7e40b5ba92ba3008b6d97a23dd5c
Databáze: OpenAIRE
Popis
Abstrakt: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 [40] 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.&nbsp
ISSN:21476799
DOI:10.18201/ijisae.2021473637