A Fuzzy Rough Hybrid Decision Making Technique for Identifying the Infected Population of COVID-19

Abstract

Decision theoretic rough set model have been used over many years in most of the application areas. It provides a novel way to knowledge acquisition, especially when dealing with vagueness and uncertainty. Many mathematical modelling 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 article. In this paper, we have proposed a novel approach of three ways 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 treatment in an emergency situation. The significance of proposed hybrid model has been discussed by presenting a comparative study and reported along with justifications too.