A rational optimal block hybrid method for enhanced accuracy in solving Lane-Emden equations DOI Creative Commons
S. S. Motsa, Salma Ahmedai,

Mpho Mendy Nefale

et al.

Partial Differential Equations in Applied Mathematics, Journal Year: 2024, Volume and Issue: unknown, P. 101003 - 101003

Published: Nov. 1, 2024

Language: Английский

A novel radial basis neural network for the Zika virus spreading model DOI
Zulqurnain Sabir,

Tino Bou Rada,

Zeinab Kassem

et al.

Computational Biology and Chemistry, Journal Year: 2024, Volume and Issue: 112, P. 108162 - 108162

Published: July 26, 2024

Language: Английский

Citations

10
Intelligent neural computing to investigate the heat and mass transmission in nanofluidic system between two rotating permeable disks: Supervised learning mechanism DOI Creative Commons
Ahmed M. Galal, Qusain Haider, Mubashar Arshad

et al.

Case Studies in Thermal Engineering, Journal Year: 2024, Volume and Issue: 59, P. 104531 - 104531

Published: May 14, 2024

The prime objective of the present study is to investigate effectiveness and accuracy a single-trained artificial neural network. Levenberg-Marquardt Backpropagated networks are tested for heat mass transmission in magnetized hybrid nanofluid flow between rotating permeable system. reference data generate different cases distinct scenarios has been obtained using Adams method Mathematica ND-Solver function. Additionally, system highly nonlinear PDE's achieved transformed into ODE's. effect body forces such as thermophoresis particle diffusion Brownian motion incorporated Configuration under observation constant impact magnetic field. Rosseland thermal radiation approximation relation utilized linear on velocity temperature profile. proposed ANNLMB depicted with performance demonstrations. Mean square error, histogram regression plots generated all discuss varying key parameters ANNLMB. Furthermore, distributed following manner 82%, 9%, 9% training, testing, validation, respectively.

Language: Английский

Citations

7
A Bayesian regularization intelligent computing scheme for the fractional dengue virus model DOI Creative Commons
Manoj Gupta, Pattarasinee Bhattarakosol

Egyptian Informatics Journal, Journal Year: 2025, Volume and Issue: 29, P. 100606 - 100606

Published: Jan. 8, 2025

Language: Английский

Citations

0
Novel machine intelligent expedition with adaptive autoregressive exogenous neural structure for nonlinear multi-delay differential systems in computer virus propagation DOI
Nabeela Anwar,

Aqsa Saddiq,

Muhammad Asif Zahoor Raja

et al.

Engineering Applications of Artificial Intelligence, Journal Year: 2025, Volume and Issue: 146, P. 110234 - 110234

Published: Feb. 20, 2025

Language: Английский

Citations

0
Novel design of artificial intelligence-based neural networks for the dynamics of magnetized chemically reactive Darcy–Forchheimer nanofluid flow DOI Creative Commons

Zohaib Arshad,

Zahoor Shah, Muhammad Asif Zahoor Raja

et al.

Journal of Thermal Analysis and Calorimetry, Journal Year: 2024, Volume and Issue: 149(24), P. 15243 - 15276

Published: Dec. 1, 2024

Language: Английский

Citations

2
A reliable neural network procedure for the novel sixth-order nonlinear singular pantograph differential model DOI
Zulqurnain Sabir, Muhammad Umar, Soheil Salahshour

et al.

Modern Physics Letters B, Journal Year: 2024, Volume and Issue: unknown

Published: July 27, 2024

An innovative singular nonlinear sixth-order (SNSO) pantograph differential model (PDM), known as the SNSO-PDM, is subject of this novel study along with its numerical investigation. The concepts and conventional Emden-Fowler have been presented in design SNSO-PDM. models based on Emden–Fowler huge applications mathematics engineering are always difficult to solve due singularity. For each class singularity, shape factors described. A reliable stochastic Levenberg-Marquardt backpropagation neural network (LMBPNN) procedure designed for correctness SNSOs-PDM observed through comparison performances achieved reference outputs. obtained results SNSO-PDM considered by applying process training, certification, testing reduce mean square error. To authenticate efficacy solutions depicted sense regression, error histograms correlation.

Language: Английский

Citations

1
Intelligent computing framework to analyze the transmission risk of COVID-19: Meyer wavelet artificial neural networks DOI
Kottakkaran Sooppy Nisar,

Iqra Naz,

Muhammad Asif Zahoor Raja

et al.

Computational Biology and Chemistry, Journal Year: 2024, Volume and Issue: 113, P. 108234 - 108234

Published: Oct. 2, 2024

Language: Английский

Citations

1
Data Collector Selection Ranking-Based Method for Collaborative Multi-Tasks in Ubiquitous Environments DOI Creative Commons

Belal Z. Hassan,

Ahmed A. A. Gad-Elrab, Mohamed S. Farag

et al.

Al-Azhar Bulletin of Science, Journal Year: 2024, Volume and Issue: 35(2)

Published: May 10, 2024

In Ubiquitous Computing and the Internet of Things, sensing control objects involve numerous devices collecting transmitting data. However, connecting these without fostering collaboration leads to suboptimal system performance. As number connected in Things increases, efficient task accomplishment through becomes imperative. This paper proposes a Data Collector Selection Method for Collaborative Multi-Tasks address this challenge, considering preferences uncertainty data collectors' contributions. The proposed method incorporates three key aspects: (1) Using Fuzzy Analytical Hierarchy Process determine optimal weights preferences; (2) Ranking collectors with Technique Order Preference by Similarity Ideal Solution based on determined weights; (3) Introducing Contribution Density as metric measure an individual collector's contribution specific task. Extensive experiments validate efficacy strategy, demonstrating superior performance balancing profit collector rewards, well overall satisfaction scores compared existing approaches.

Language: Английский

Citations

0
Physics‐informed neural networks guided modelling and multiobjective optimization of a mAb production process DOI

Md Nasre Alam,

Anurag Anurag, Neelesh Gangwar

et al.

The Canadian Journal of Chemical Engineering, Journal Year: 2024, Volume and Issue: unknown

Published: Aug. 1, 2024

Abstract In this paper, we aim to correlate various process and product quality attributes of a mammalian cell culture with parameters. To achieve this, employed physics‐informed neural networks that solve the governing ordinary differential equations comprising independent variables (inputs‐ time, flow rates, volume) dependent (outputs‐ viable density, dead glucose concentration, lactate monoclonal antibody concentration). The proposed model surpasses prediction accuracy capabilities other commonly used modelling approaches, such as multilayer perceptron model. It has higher R ‐squared ( 2 ), lower root mean square error, absolute error than for all output (viable viability, Furthermore, incorporate Bayesian optimization study maximize density concentration. Single objective weighted sum multiobjective were carried out concentration in separate (single optimization) combined (multiobjective forms. An increment 13.01% 18.57% respectively, projected under single optimization, 46.32% 67.86%, compared base case. This highlights potential networks‐based upstream processing cell‐based antibodies biopharmaceutical operations.

Language: Английский

Citations

0
A novel policy for coordinating a hurricane monitoring system using a swarm of buoyancy-controlled balloons trading off communication and coverage DOI
Bruno R.O. Floriano, Blaine Hanson, Thomas Bewley

et al.

Engineering Applications of Artificial Intelligence, Journal Year: 2024, Volume and Issue: 139, P. 109495 - 109495

Published: Oct. 30, 2024

Language: Английский

Citations

0