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A fuzzy rough hybrid decision making technique for identifying the infected population of COVID-19
Sandip Majumder1, Samarjit Kar1, Eshan Samanta2
1National Institute of Technology, Durgapur, 713209 India.
Abstract:
Decision theoretic rough set model have been used over many years in most of the application areas. It provides a novel way for knowledge acquisition, especially when dealing with vagueness and uncertainty. Many mathematical modelings have been presented recently to control the pandemic nature of COVID-19 and along with its control model as well. Decision-based treatment recommendation has not yet been found so far in any of the articles. In this paper, we have proposed a novel approach of three-way decision based on linguistic information of a COVID-19 susceptible person. To present this, we have discussed the probabilistic rough fuzzy hybrid model with linguistic information. This model helps us to guess the infected person and decide whom to send for self-isolation, home quarantine and medical treatment in an emergency situation. The significance of the proposed hybrid model has been discussed by presenting a comparative study and reported along with justifications too.

