In this work, three-dimensional nonlinear food chain system is numerically treated using the
computational heuristic framework of artificial neural networks (ANNs) together with the …

In the presented article, a stochastic network paradigm through Bayesian Regularization
backpropagation neural network (BRB-NN) is designed to interpret the dynamics of the …

The current work is related to present the solutions of the corneal shape-based eye surgery
model (CSESM) by applying the novel procedures of Gudermannian neural network (GNN) …

The aim of this work is to present the numerical simulations of the novel designed fractional
order Leptospirosis model (FOLM) by using the strength of stochastic numerical supervised …

The purpose of the current work is to solve the SIR nonlinear model based on dengue fever
using a stochastic numerical computing scheme together with the artificial neural networks …

This current study presents a nonlinear system of the hepatitis B virus infection by using the
strength of artificial neural network (ANN) together with the competences of global and local …

The focus of the present study is to present a stochastic numerical computing framework
based on Gudermannian neural networks (GNNs) together with the global and local search …

In this study, a novel heuristic computing technique is presented to solve bioinformatics
problem for the corneal shape model of eye surgery using Morlet wavelet artificial neural …

This study indicates the design of swarming procedure based on the stochastic framework of
artificial neural networks (ANNs) along with the particle swarm optimization (PSO) and …

The motive of these investigations is to present the numerical performances of the fractional
order mathematical influenza disease model (FO-MIDM) by designing the computational …