2023

Akkilic Ayse Nur; Sabir Zulqurnain; Bhat Shahid Ahmad; Bulut Hasan

The motive of this work is to provide the numerical performances of the monkeypox transmission 32 mathematical model by using a novel deep neural network process with eleven and twenty-two neurons in the 33 hidden layers. The purpose to provide the deep neural network stochastic process is to obtain more accurate 34 solutions of the monkeypox transmission mathematical system. This process is enhanced by using an 35 activation radial basis function in both layers for solving the monkeypox transmission mathematical model 36 along with the implementation of the Bayesian regularization optimization scheme. The presentation of the 37 mathematical dynamical model has two categories, human and rodent. The human dynamics is classified into, 38 susceptible, exposed, infectious, clinically ill human and recovered individuals. The rodent is divided into 39 three forms, susceptible, exposed, and infected. A dataset is presented with the Adam approach that is 40 processed using the training, testing, and certification procedure by taking the data as 0.13, 0.12 and 0.15. The 41 correctness is observed through the matching of the results and the statistical plots are plotted using the 42 regression, state transition, error histograms and correlation.