In the present study, stochastic numerical computing approach is developed by applying
artificial neural networks (ANNs) to compute the solution of Lane–Emden type boundary …

In this article, an efficient computing technique has been developed for the solution of
fractional order systems governed with initial value problems (IVPs) of the Bagley–Torvik …

In this research, the well-known non-linear Lane–Emden–Fowler (LEF) equations are
approximated by develo** a nature-inspired stochastic computational intelligence …

In this study, a computational intelligence technique based on three different designs of
artificial neural networks (ANNs) is presented to solve the nonlinear Troesch's boundary …

The importance of rectangular porous fins for the transformation of heat through the system
is well-recognized to analyze the physical characteristics of material in practical …

In this paper, a neuro-heuristic technique by incorporating artificial neural network models
(NNMs) optimized with sequential quadratic programming (SQP) is proposed to solve the …

Numerical simulation of fluids is crucial in modeling physical phenomena in various fields,
including engineering, physics, and environmental science. Fluids are typically described by …

This study reports novel hybrid computational methods for the solutions of nonlinear singular
Lane–Emden type differential equation arising in astrophysics models by exploiting the …

In the present study, a new soft computing framework is developed for solving nanofluidic
problems based on fluid flow and heat transfer of multi-walled carbon nanotube (MWCNT) …

In this article, examine the performance of a physics informed neural networks (PINN)
intelligent approach for predicting the solution of non-linear Lorenz differential equations …