Open Access iconOpen Access

ARTICLE

Numerical Procedure for Fractional HBV Infection with Impact of Antibody Immune

Sakda Noinang1, Zulqurnain Sabir2, Muhammad Asif Zahoor Raja3, Soheil Salahshour4, Wajaree Weera5,*, Thongchai Botmart5

1 Department of Mathematics Statistics and Computer, Faculty of Science, Ubon Ratchathani University, Ubon Ratchathani, 34190, Thailand
2 Department of Mathematics and Statistics, Hazara University, Mansehra, 21120, Pakistan
3 Future Technology Research Center, National Yunlin University of Science and Technology, Douliou, Yunlin, 64002, Taiwan
4 Faculty of Engineering and Natural Sciences, Bahcesehir University, Istanbul, 34494, Turkey
5 Department of Mathematics, Faculty of Science, Khon Kaen University, Khon Kaen, 40002, Thailand

* Corresponding Author: Wajaree Weera. Email: email

Computers, Materials & Continua 2023, 74(2), 2575-2588. https://doi.org/10.32604/cmc.2023.029046

Abstract

The current investigations are presented to solve the fractional order HBV differential infection system (FO-HBV-DIS) with the response of antibody immune using the optimization based stochastic schemes of the Levenberg-Marquardt backpropagation (LMB) neural networks (NNs), i.e., LMBNNs. The FO-HBV-DIS with the response of antibody immune is categorized into five dynamics, healthy hepatocytes (H), capsids (D), infected hepatocytes (I), free virus (V) and antibodies (W). The investigations for three different FO variants have been tested numerically to solve the nonlinear FO-HBV-DIS. The data magnitudes are implemented 75% for training, 10% for certification and 15% for testing to solve the FO-HBV-DIS with the response of antibody immune. The numerical observations are achieved using the stochastic LMBNNs procedures for soling the FO-HBV-DIS with the response of antibody immune and comparison of the results is presented through the database Adams-Bashforth-Moulton approach. To authenticate the validity, competence, consistency, capability and exactness of the LMBNNs, the numerical presentations using the mean square error (MSE), error histograms (EHs), state transitions (STs), correlation and regression are accomplished.

Keywords


Cite This Article

APA Style
Noinang, S., Sabir, Z., Raja, M.A.Z., Salahshour, S., Weera, W. et al. (2023). Numerical procedure for fractional HBV infection with impact of antibody immune. Computers, Materials & Continua, 74(2), 2575-2588. https://doi.org/10.32604/cmc.2023.029046
Vancouver Style
Noinang S, Sabir Z, Raja MAZ, Salahshour S, Weera W, Botmart T. Numerical procedure for fractional HBV infection with impact of antibody immune. Comput Mater Contin. 2023;74(2):2575-2588 https://doi.org/10.32604/cmc.2023.029046
IEEE Style
S. Noinang, Z. Sabir, M.A.Z. Raja, S. Salahshour, W. Weera, and T. Botmart "Numerical Procedure for Fractional HBV Infection with Impact of Antibody Immune," Comput. Mater. Contin., vol. 74, no. 2, pp. 2575-2588. 2023. https://doi.org/10.32604/cmc.2023.029046



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
  • 1015

    View

  • 584

    Download

  • 0

    Like

Share Link