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A Decision-Making Approach to Optimize COVID-19 Treatment Strategy under a Conjunctive Complex Fuzzy Environment.

Authors :
Faraz, Muhammad Iftikhar
Alhamzi, Ghaliah
Imtiaz, Aneeza
Masmali, Ibtisam
Shuaib, Umer
Razaq, Abdul
Razzaque, Asima
Source :
Symmetry (20738994). Jul2023, Vol. 15 Issue 7, p1370. 26p.
Publication Year :
2023

Abstract

Symmetry is a key part of the study of basic forces and particles, as well as the creation of mathematical models that help scientists in various scientific disciplines understand complex events. Scientists can figure out what a system is made of and how it works by looking at its symmetry. They can then use this information to make predictions and create new materials and technologies. Humanity has conquered many once-fatal diseases due to medical research and technological advancements. Although this progress is encouraging, there are still a great many areas that require continual human efforts. An effort is made in this article to choose the best treatment strategy to completely manage the pandemic of COVID-19 under conjunctive complex fuzzy knowledge. In this paper, the concept of conjunctive complex fuzzy relations is presented and numerous set theoretical aspects of this phenomenon are established. The investigation of this ideology is further expanded to describe different sorts of essential structural conjunctive complex fuzzy relations. Matrix and graphical representations of the formation of these newly specified relations are also provided. Moreover, this concept has been successfully employed to provide a therapy strategy for a rapid recovery from COVID-19. Furthermore, a comparative analysis is conducted to demonstrate the validity and applicability of the suggested approaches compared to existing methods. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20738994
Volume :
15
Issue :
7
Database :
Academic Search Index
Journal :
Symmetry (20738994)
Publication Type :
Academic Journal
Accession number :
169700174
Full Text :
https://doi.org/10.3390/sym15071370