Soft -Rough Set and Its Applications in Decision Making of Coronavirus

Abstract

In this paper, we present a proposed method for generating a soft rough approximation as a modification and generalization of Zhaowen et al. approach. Comparisons were obtained between our approach and the previous study and also. Eventually, an application on Coronavirus (COVID-19) has been presented, illustrated using our proposed concept, and some influencing results for symptoms of Coronavirus patients have been deduced. Moreover, following these concepts, we construct an algorithm and apply it to a decision-making problem to demonstrate the applicability of our proposed approach. Finally, a proposed approach that competes with others has been obtained, as well as realistic results for patients with Coronavirus. Moreover, we used MATLAB programming to obtain the results; these results are consistent with those of the World Health Organization and an accurate proposal competing with the method of Zhaowen et al. has been studied. Therefore, it is recommended that our proposed concept be used in future decision making.

Rough fuzzy-topological approximation space with tooth decay in decision making

“…Pawlak [11] established the rough set theory in 1982 as a new mathematical technique or simple tools for dealing with ambiguity in knowledge-based systems and data dissection. This theory has numerous applications in process control, economics, medical diag-nosis, chemistry, psychology, finance, marketing, biochemistry, environmental science, intelligent agents, image analysis, biology, conflict analysis, telecommunications, and other domains, [12][13][14][15]. The 2016 Nobel Prize in Physics was awarded to international schools in Germany and the United States, for the theory of matter transformation that used topological applications of science and engineering [16].…”