A numerical treatment through Bayesian regularization neural network for the chickenpox disease model.

Objectives: The current research investigations designates the numerical solutions of the chickenpox disease model by applying a proficient optimization framework based on the artificial neural network. The mathematical form of the chickenpox disease model is divided into different categories of individuals, susceptible, vaccinated, infected, exposed, recovered, and infected with/without complications.

Method: The construction of neural network is performed by using the single hidden layer and the optimization of Bayesian regularization.