Integrated intelligent computing with neuro-swarming solver for multi-singular fourth-order nonlinear Emden–Fowler equation
In the present work, a novel neuro-swarming based heuristic solver is established for the
numerical solutions of fourth-order multi-singular nonlinear Emden–Fowler (FO-MS-NEF) …
numerical solutions of fourth-order multi-singular nonlinear Emden–Fowler (FO-MS-NEF) …
Computational intelligence of Levenberg-Marquardt backpropagation neural networks to study thermal radiation and Hall effects on boundary layer flow past a …
In the present investigation, an integrated numerical computing through neural networks
which are backpropagated with Levenberg-Marquard scheme (NN-BLMS) is designed for …
which are backpropagated with Levenberg-Marquard scheme (NN-BLMS) is designed for …
[HTML][HTML] An efficient stochastic numerical computing framework for the nonlinear higher order singular models
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 …
based on Gudermannian neural networks (GNNs) together with the global and local search …
Fractional mayer neuro-swarm heuristic solver for multi-fractional order doubly singular model based on lane–emden equation
This research is related to present a novel fractional Mayer neuro-swarming intelligent
solver for the numerical treatment of multi-fractional order doubly singular Lane–Emden (LE) …
solver for the numerical treatment of multi-fractional order doubly singular Lane–Emden (LE) …
Meyer wavelet neural networks to solve a novel design of fractional order pantograph Lane-Emden differential model
The aim of this study is to design a singular fractional order pantograph differential model by
using the typical form of the Lane-Emden model. The necessary details of the singular-point …
using the typical form of the Lane-Emden model. The necessary details of the singular-point …
[HTML][HTML] Heuristic computational design of Morlet wavelet for solving the higher order singular nonlinear differential equations
The aim of this study is to present the numerical solutions of the higher order singular
nonlinear differential equations using an advanced intelligent computational approach by …
nonlinear differential equations using an advanced intelligent computational approach by …
A hybrid swarming computing approach to solve the biological nonlinear Leptospirosis system
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 …
artificial neural networks (ANNs) along with the particle swarm optimization (PSO) and …
Design of morlet wavelet neural network for solving a class of singular pantograph nonlinear differential models
The aim of this study is to design a layer structure of feed-forward artificial neural networks
using the Morlet wavelet activation function for solving a class of pantograph differential …
using the Morlet wavelet activation function for solving a class of pantograph differential …
Intelligent Bayesian regularization networks for bio-convective nanofluid flow model involving gyro-tactic organisms with viscous dissipation, stratification and heat …
In the current study, a novel intelligent numerical computing paradigm based upon the
foundation of the artificial neural networks legacy involving the Bayesian regularization …
foundation of the artificial neural networks legacy involving the Bayesian regularization …
[PDF][PDF] Numerical investigations of the nonlinear smoke model using the Gudermannian neural networks
These investigations are to find the numerical solutions of the nonlinear smoke model to
exploit a stochastic framework called gudermannian neural works (GNNs) along with the …
exploit a stochastic framework called gudermannian neural works (GNNs) along with the …