Topological Models of Rough Sets and Decision Making of COVID-19

• Main Authors: El Atik, A.E.F (Author), El-Gayar, M.A (Author)
• Format: Article
• Language: English
• Published: Hindawi Limited 2022
• Subjects: Binary relation; Closure operators; Coronaviruses; COVID-19; Decision making; Decision-making process; Decisions makings; Equivalence relations; Medical applications; Neighbourhood; Rough set theory; Topological models; Topological reduction; Topological techniques; Topology
• Online Access: View Fulltext in Publisher

 The basic methodology of rough set theory depends on an equivalence relation induced from the generated partition by the classification of objects. However, the requirements of the equivalence relation restrict the field of applications of this philosophy. To begin, we describe two kinds of closure operators that are based on right and left adhesion neighbourhoods by any binary relation. Furthermore, we illustrate that the suggested techniques are an extension of previous methods that are already available in the literature. As a result of these topological techniques, we propose extended rough sets as an extension of Pawlak's models. We offer a novel topological strategy for making a topological reduction of an information system for COVID-19 based on these techniques. We provide this medical application to highlight the importance of the offered methodologies in the decision-making process to discover the important component for coronavirus (COVID-19) infection. Furthermore, the findings obtained are congruent with those of the World Health Organization. Finally, we create an algorithm to implement the recommended ways in decision-making. © 2022 Mostafa A. El-Gayar and Abd El Fattah El Atik.