Fuzzy Logic Modeling of Covit-19 Mask and Social Distance
Abstract:
As a result of Covit-19 epidemics there are multiple vulnerabilities in a society. The COVID-19 outbreak has revealed multiple vulnerabilities in community systems. Inequalities may not only make containment challenging, but also result in infectious virus, which may cause to social distancing policies improper implementations in isolation from economic support mechanisms. It is necessary to address these vulnerabilities and provide local resilience improvements leading to sustainability integration by consideration of the basic requirements such as the social distance maintenance and musk wearing. The current study yields a fuzzy modeling inference system for mask wear and social distance variables effects on the disease based on some real and hypothetical data leading to potential disease uncertainty contents through membership degrees. This paper provides a fuzzy logic modeling to relate the social distance and musk wearing precautions to the epidemic ratio of the pandemic. A fuzzy inference system modeling is proposed to predict the impacts of mask wearing and social distance on the COVIT-19 disease possibility. The model digests uncertainties in all the input and output variables in a systematic manner for rational inferences.
