A radial basis neural network for the diarrhea disease model including treatment and vaccination
J.F. Gómez-Aguilar·J. Torres-Jimenez·V.H. Olivares-Peregrino·Eduardo Pérez Careta·Jose R. Razo-Hernandez·J.E. Lavin-Delgado
The aim of this study is to propose a stochastic radial basis (RB) artificial neural network (ANN) and the scale conjugate gradient (SCG) called as RB-ANN-SCG for the the diarrhea disease model including treatment and vaccination (DDMTV). The diarrhea disease system is basically a susceptible, infected and recovered model that includes the factor of treatment and vaccination. The dataset is obtained by using the Adam solver, which lessens the mean square error with the distribution of testing (1