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Decision-making analysis of minimizing the death rate due to covid-19 by using q-rung orthopair fuzzy soft bonferroni mean operator

Document Type : Research Paper

Authors

1 Department of Mathematics, Government College University, Lahore 54000, Pakistan.

2 Department of Mathematics and Applied Mathematics, University of Pretoria 0002, South Africa.

3 Department of Computer Science, University of Illinois at Springfield, One University Plaza, Springfield, IL 62703, USA.

Abstract

The q-Rung Orthopair Fuzzy Soft Set (q-ROFSS) theory is a significant extension of Pythagorean fuzzy soft set and intuitionistic fuzzy soft set theories for dealing with the imprecision and uncertainty in data. The purpose of this study is to improve and apply this theory in decision-making. To achieve this purpose, we firstly propose some Bonferroni Mean (BM) and Weighted Bonferroni Mean (WBM) aggregation operators for aggregating the data. Some desired properties are presented in detail and the existing aggregation operators are used as distinct cases of our proposed operators. Further, a decision-making analysis is presented based on our proposed operations and applied to decision-making in COVID-19 diagnosis. The preferred way is discussed to protect maximum human lives from COVID-19. A numerical example is given to support the claim. The experimental results demonstrate the proposed operators have an ability to make a precise decision with imprecision and uncertain information which will find a broad application in the decision-making area.

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Journal of Fuzzy Extension and Applications
Volume 3, Issue 3
July 2022
Pages 231-248
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