Soft rough set theory has been presented as a basic mathematical model for decision-making for many real-life data. However, soft rough sets are based on a possible fusion of rough sets and soft sets which were proposed by Feng et al. . The main contribution of the present article is to introduce a modification and a generalization for Feng's approximations, namely, soft $\beta$-rough approximations, and some of their properties will be studied. A comparison between the suggested approximations and the previous one  will be discussed. Some examples are prepared to display the validness of these proposals. Finally, we put an actual example of the infections of coronavirus (COVID-19) based on soft $\beta$-rough sets. This application aims to know the persons most likely to be infected with COVID-19 via soft $\beta$-rough approximations and soft $\beta$-rough topologies.
COVID-19, information system, soft sets, soft topological spaces, decision-making
BABLY, MOSTAFA K. EL and ATIK, ABD EL FATTAH A. EL
"Soft $\beta$-rough sets and their application to determine COVID-19,"
Turkish Journal of Mathematics: Vol. 45:
3, Article 4.
Available at: https://journals.tubitak.gov.tr/math/vol45/iss3/4