An efficient computational procedure to solve the biological nonlinear Leptospirosis model using the genetic algorithms
The purpose of this work is to present the numerical solutions of the nonlinear mathematical
Leptospirosis disease (LD) model using the computational performances of the artificial …
Leptospirosis disease (LD) model using the computational performances of the artificial …
[HTML][HTML] Intelligent computing paradigm for unsteady magneto nano-polymeric Casson nanofluid with Ohmic dissipation and thermal radiation
In this present investigative mode of study, a biological innovational approach is adopted in
the form of an intelligent computing paradigm to investigate the properties of flow in the case …
the form of an intelligent computing paradigm to investigate the properties of flow in the case …
Novel Bayesian distributed adaptive neural structure for titanium and aluminium alloy nanofluidic model with gyrotactic microorganisms
The purpose of this research study is to evaluate the solutions of Titanium and Aluminum
alloy nanofluidic model with gyrotactic microorganisms (TAA-NFMGM) by applying …
alloy nanofluidic model with gyrotactic microorganisms (TAA-NFMGM) by applying …
Design of Bayesian stochastic networks for numerical treatment of Williamson fluid stretching flow model with mixed convected heat generation
In the presented article, a stochastic network paradigm through Bayesian Regularization
backpropagation neural network (BRB-NN) is designed to interpret the dynamics of the …
backpropagation neural network (BRB-NN) is designed to interpret the dynamics of the …
Novel design of recurrent neural network for the dynamical of nonlinear piezoelectric cantilever mass–beam model
Piezoelectricity spans a wide range of fields, showcasing its practical significance. In the
realm of consumer electronics, piezoelectric materials are utilized in buzzers, sensors, and …
realm of consumer electronics, piezoelectric materials are utilized in buzzers, sensors, and …
Numerical treatment of singular functional systems in quantum calculus: adaptive backpropagated Levenberg–Marquardt neural networks
The purpose of this research is to investigate the numerical solutions of singular functional
delay differential equations (SFDDEs) of third, fourth and fifth orders, which arises in …
delay differential equations (SFDDEs) of third, fourth and fifth orders, which arises in …
[HTML][HTML] Thermal and mass exchange in a multiphase peristaltic flow with electric-debye-layer effects and chemical reactions using machine learning
The present investigation delves into the analysis of mass and thermal transmission during
the peristalsis of a two phase flow of a Prandtl fluid, within a symmetric channel by …
the peristalsis of a two phase flow of a Prandtl fluid, within a symmetric channel by …
Gudermannian Neural Networks for Two-Point Nonlinear Singular Model Arising in the Thermal-Explosion Theory
The goal of this research is to design the Gudermannian neural networks (GNNs) to solve a
type of two-point nonlinear singular boundary value problems (TPN-SBVPs) that arise within …
type of two-point nonlinear singular boundary value problems (TPN-SBVPs) that arise within …
Intelligent computing infrastructure for nodal/saddle stagnation point slip flow of an aqueous convectional magnesium oxide–gold hybrid nanofluid with viscous …
Using the power of numerical computation through Levenberg Marquardt backpropagation
(LMB), the fluidic issue in the present study has features of heat transfer by convection in the …
(LMB), the fluidic issue in the present study has features of heat transfer by convection in the …
Design of Neuro-Stochastic Bayesian Networks for Nonlinear Chaotic Differential Systems in Financial Mathematics
The research community's treatise on computational economics and financial models has
promising interest for the exploration and exploitation of artificial intelligence (AI)-based …
promising interest for the exploration and exploitation of artificial intelligence (AI)-based …