New analytical and numerical solutions to the (2+ 1)-dimensional conformable cpKP–BKP equation arising in fluid dynamics, plasma physics, and nonlinear optics
Abstract This study investigates the (2+ 1)-dimensional conformable combined potential
Kadomtsev–Petviashvili-B-type Kadomtsev–Petviashvili (cpKP–BKP) equation. It is a linear …
Kadomtsev–Petviashvili-B-type Kadomtsev–Petviashvili (cpKP–BKP) equation. It is a linear …
[HTML][HTML] Investigation of the hyperchaos and control in the fractional order financial system with profit margin
This research study proposes a novel hyperchaotic finance system with profit margin and
then utilizes the Adomian Decomposition Method (ADM) to tackle the solution of the …
then utilizes the Adomian Decomposition Method (ADM) to tackle the solution of the …
Fractional optimal control model and bifurcation analysis of human syncytial respiratory virus transmission dynamics
In this paper, the Caputo-based fractional derivative optimal control model is looked at to
learn more about how the human respiratory syncytial virus (RSV) spreads. Model solution …
learn more about how the human respiratory syncytial virus (RSV) spreads. Model solution …
Scaled conjugate gradient for the numerical simulations of the mathematical model-based monkeypox transmission
The current study presents the numerical solutions of a fractional order monkeypox virus
model. The fractional order derivatives in the sense of Caputo are applied to achieve more …
model. The fractional order derivatives in the sense of Caputo are applied to achieve more …
Reactor temperature prediction method based on CPSO-RBF-BP neural network
X Tang, B Xu, Z Xu - Applied Sciences, 2023 - mdpi.com
A neural network model based on a chaotic particle swarm optimization (CPSO) radial basis
function-back propagation (RBF-BP) neural network was suggested to improve the accuracy …
function-back propagation (RBF-BP) neural network was suggested to improve the accuracy …
A Bayesian regularization neural network procedure to solve the language learning system
The aim of this research is to provide the numerical performances of the language learning
system (LLS) by applying the process of Bayesian regularization neural network (BRNN) …
system (LLS) by applying the process of Bayesian regularization neural network (BRNN) …
Fast and Scaled Counting-Based Stochastic Computing Divider Design
This article presents novel designs for stochastic computing (SC)-based dividers, which
promise low latency, high energy efficiency as well as high accuracy for error-tolerant …
promise low latency, high energy efficiency as well as high accuracy for error-tolerant …
[PDF][PDF] Machine Learning Empowered Security and Privacy Architecture for IoT Networks with the Integration of Blockchain.
ABSTRACT The Internet of Things (IoT) is growing rapidly and impacting almost every
aspect of our lives, from wearables and healthcare to security, traffic management, and fleet …
aspect of our lives, from wearables and healthcare to security, traffic management, and fleet …
Designing the sinc neural networks to solve the fractional optimal control problem
R Heydari Dastjerdi, G Ahmadi - Iranian Journal of Numerical …, 2024 - ijnao.um.ac.ir
Sinc numerical methods are essential approaches to solving nonlinear problems. In this
work, based on this method, the sinc neural networks (SNNs) are designed and applied to …
work, based on this method, the sinc neural networks (SNNs) are designed and applied to …
Numerical Investigation of Hall and Ion Slip Effects on Prandtl Nanofluid with Non-Fourier Double Diffusion Theories: Artificial Neural Network Approach for Thermal …
S Habib, Z Khan, S Islam - 2023 - researchsquare.com
To model complex relationships between input and output data,(ANN) algorithms are
extensively used in engineering and fluid mechanics. They are able to predict outcomes …
extensively used in engineering and fluid mechanics. They are able to predict outcomes …