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• W4297542442 startingPage "3514" @default.
• W4297542442 abstract "In order to help curb the spread of the COVID-19 pandemic, this paper develops a multi-attribute decision-making framework for COVID-19 vaccine evaluation based on their major clinical characteristics and efficacy. Firstly, a new multi-criteria Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) modification has been constructed in an interval-valued Fermatean fuzzy (IVFF) environment, improving the shortcomings of traditional TOPSIS. Secondly, a new conceptual framework for static and dynamic evaluation of COVID-19 vaccines has been built. The proposed methodology incorporates a variety of crisp and fuzzy MCDM methods. The analysis of the results of two practical examples shows that the new framework for vaccine comparison is feasible and effective, and finally, some recommendations for enhancement of government anti-COVID-19 strategies are suggested." @default.
• W4297542442 created "2022-09-29" @default.
• W4297542442 creator A5050199179 @default.
• W4297542442 creator A5054211196 @default.
• W4297542442 date "2022-09-26" @default.
• W4297542442 modified "2023-10-09" @default.
• W4297542442 title "Extension of Interval-Valued Fermatean Fuzzy TOPSIS for Evaluating and Benchmarking COVID-19 Vaccines" @default.
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• W4297542442 doi "https://doi.org/10.3390/math10193514" @default.
• W4297542442 hasPublicationYear "2022" @default.
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