Todim-Vikor Methods with Pythagorean Fuzzy Information Based Emergency Decision Support Model for Economic Growth Factor Selection
13th International Conference on Cloud Computing, Data Science and Engineering, Confluence 2023
; : 340-345, 2023.
Article
in English
| Scopus | ID: covidwho-2280601
ABSTRACT
Because India's economy has shrunk to a low level during COVID-19, building an emergency decision support model (EDSM) for economic growth factors is the main objective of this study. We develop the TODIM-VIKOR method under Pythagorean fuzzy information. For dealing with comparison problems, the Pythagorean fuzzy scoring function is presented. We also include a new entropy metric for assessing the degree of fuzziness in PyFS. We also present a new Jensen Shannon divergence metric for PyFS that can be used to compare the discrimination information of two PyFSs. In this article, we introduced entropy and divergence measures to derive objective weight in the TODIM-VIKOR approach. Establishes a novel emergency decision making (EDM) strategy under the Pythagorean fuzzy atmosphere, using economic growth considerations. We used TODIM to determine the overall dominance degree, which takes into account the bounded rationality of decision makers, and VIKOR to calculate the compromise ranking of alternatives. © 2023 IEEE.
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Scopus
Language:
English
Journal:
13th International Conference on Cloud Computing, Data Science and Engineering, Confluence 2023
Year:
2023
Document Type:
Article
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