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Intelligent Computing Paradigm For Second-Grade Fluid In A Rotating Frame In A Fractal Porous Medium

Author

Listed:
  • 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)

  • ALI AKGÃœL

    (�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)

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.

Suggested Citation

  • Mohammad Kanan & Habib Ullah & Muhammad Asif Zahoor Raja & Mehreen Fiza & Hakeem Ullah & Muhammad Shoaib & Ali Akgãœl & Jihad Asad, 2023. "Intelligent Computing Paradigm For Second-Grade Fluid In A Rotating Frame In A Fractal Porous Medium," FRACTALS (fractals), World Scientific Publishing Co. Pte. Ltd., vol. 31(08), pages 1-22.
    • Handle: RePEc:wsi:fracta:v:31:y:2023:i:08:n:s0218348x23401758
    DOI: 10.1142/S0218348X23401758
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