ABSTRACT The numerical simulations of diarrhea disease with treatment and vaccination system (DDTVS) by applying the artificial computational procedure are presented in this study. These stochastic computing neural network performances have been applied along with the Bayesian regularization computing scheme (BRCS) for the nonlinear DDTVS. The mathematical form of the diarrhea disease presents a nonlinear system based on the susceptible, infected, and recovered model, along with the treatment and vaccination factors. The neural network procedures are applied by applying twenty neurons, a log‐sigmoid activation function, and the data distribution is provided as 78% for training, while the other two statistics, validation and testing, have been taken as 12%. The designed neural network approach's correctness is observed by the overlapping of source and obtained solutions, as well as the reducible absolute error. Additionally, the dependability and trustworthiness of the proposed neural network structure is examined by using function fitness, histogram measures, and correlation/regression.
Chand et al. (Thu,) studied this question.