INTELLIGENT COMPUTING PARADIGM FOR SECOND-GRADE FLUID IN A ROTATING FRAME IN A FRACTAL POROUS MEDIUM

Mohammad Kanan, Habib Ullah, Muhammad Asif Zahoor Raja, Mehreen Fiza, Hakeem Ullah, Muhammad Shoaib, AKGÃœL Ali and Jihad Asad
Additional contact information
Mohammad Kanan: Jeddah College of Engineering, University of Business and Technology, Jeddah 21432, Saudi Arabia
Habib Ullah: ��Department of Mathematics, Abdul Wali Khan University, Mardan, 23200 Khyber Pakhtunkhwa, Pakistan
Muhammad Asif Zahoor Raja: ��Future Technology Research Center, National Yunlin University of Science and Technology, 123 University Road, Section 3, Douliou, Yunlin 64002, Taiwan
Mehreen Fiza: ��Department of Mathematics, Abdul Wali Khan University, Mardan, 23200 Khyber Pakhtunkhwa, Pakistan
Hakeem Ullah: ��Department of Mathematics, Abdul Wali Khan University, Mardan, 23200 Khyber Pakhtunkhwa, Pakistan
Muhammad Shoaib: �AI Centre, Yuan Ze University, Taoyun 320, Taiwan
AKGÜL Ali: �Department of Computer Science and Mathematics, Lebanese American University, Beirut, Lebanon∥Department of Mathematics, Art and Science Faculty, Siirt University, 56100 Siirt, Turkey**Department of Mathematics, Mathematics Research Center, Near East University, Ner East Boulevard PC
Jihad Asad: ��†Department of Physics, Faculty of Science, Plaestine Technical University - Kadoorie Tulkarm, P 305, P. O. Box 7, Palestine

FRACTALS (fractals), 2023, vol. 31, issue 08, 1-22

Abstract: The numerical methods such as the artificial neural networks with greater probability and nonlinear configurations are more suitable for estimation and modeling of the problem parameters. The numerical methods are easy to use in applications as these methods do not require costly and time-consuming tests like the experimental study. In this study, we use the Levenberg–Marquardt-based backpropagation Process (LMP) to create a computing paradigm that makes use of the strength of artificial neural networks (ANN), known as (ANN-LMP). Here we use the ANN-LMP to obtain the solution of the second-grade fluid in a rotating frame in a porous material with the impact of a transverse magnetic field. The 1000 data set points in the interval [0, 1] are used for the network training to determine the effect of various physical parameters of the flow problem under consideration. The experiment is executed of six scenarios with different physical paramaters. ANN-LMP is used for evaluating the mean square errors (MSE), training (TR), validation (VL), testing (TT), performance (PF) and fitting (FT) of the data. The problem has been verified by error histograms (EH) and regression (RG) measurements, which show high consistency with observed solutions with accuracy ranging from E-5 to E-8. Characteristics of various concerned parameters on the velocity and temperature profiles are studied.

Keywords: ANN-LMP; Second-grade Fluid; Porous Medium; Intelligent Computing; Error Histogram; Regression Analysis (search for similar items in EconPapers)
Date: 2023
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.worldscientific.com/doi/abs/10.1142/S0218348X23401758
Access to full text is restricted to subscribers

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wsi:fracta:v:31:y:2023:i:08:n:s0218348x23401758

Ordering information: This journal article can be ordered from

DOI: 10.1142/S0218348X23401758

Access Statistics for this article

FRACTALS (fractals) is currently edited by Tara Taylor

More articles in FRACTALS (fractals) from World Scientific Publishing Co. Pte. Ltd.
Bibliographic data for series maintained by Tai Tone Lim ().