Finite Automata Model For SEIHRD Epidemic Model Of COVID-19

  • Venkata Kalyani U., Eswarlal T., Avinash Sharma


Epidemics is a critical vicinity of situation for all living beings in the world. If  we no longer cope with a pandemic situation in a right manner,it cannot be controlled and it results in a disaster as huge quantity of human population is concerned. Here we evolve a non-deterministic finite automata (NFA) for the Susceptible-Exposed-Infectives-Hospitalized-Recovered-Death (SEIHRD) model for computational purpose. Through this version we could show there will be certain  languages which can be regular in epidemic model of automata since it is able to be compared with the languages which are normally regular, for which we are able to have NFA. We made an attempt to expose how the epidemic model could behave in order that we may better broaden our methods that could tackle this epidemic scenario. The objective of this work is to find a computation model in  terms of nondeterministic finite automata (NFA) by which we may better infer the pandemic environment.