A mathematical model of coronavirus transmission by using the heuristic computing neural networks.

In this study, the nonlinear mathematical model of COVID-19 is investigated by stochastic solver using the scaled conjugate gradient neural networks (SCGNNs). The nonlinear mathematical model of COVID-19 is represented by coupled system of ordinary differential equations and is studied for three different cases of initial conditions with suitable parametric values. This model is studied subject to seven class of human population () and individuals are categorized as: susceptible (), exposed (), quarantined (), asymptotically diseased (), symptomatic diseased () and finally the persons removed from COVID-19 and are denoted by ().