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Communications in Mathematical Biology and Neuroscience ISSN 2052-2541

Archives › Volume 2020 (2020)

Commun. Math. Biol. Neurosci. 2020 (2020), Article ID 50

Reliable iterative methods for mathematical model of COVID-19 based on data in Anhui, China

Sawsan Mohsin Abed, M.A. Al-Jawary

PDF (716.5 KB) https://doi.org/10.28919/cmbn/4802

Abstract

In this paper, five reliable iterative methods: Daftardar-Jafari method (DJM), Tamimi-Ansari method (TAM), Banach contraction method (BCM), Adomian decomposition method (ADM) and Variational iteration method (VIM) to obtain approximate solutions for a mathematical model that represented the coronavirus pandemic (COVID -19 pandemic). The accuracy of the obtained results is numerically verified by evaluating the maximum error remainder. In addition, the approximate results are compared with the fourth-order Runge-Kutta method (RK4) and good agreement have achieved. The convergence of the proposed methods is successfully demonstrated and mathematically verified. All calculations were successfully performed with MATHEMATICA®10.

Published
6 August 2020
Volume
2020 (2020)
License
CC BY 3.0

Copyright © 2020 Sawsan Mohsin Abed, M.A. Al-Jawary. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Cite this article

S. M. Abed, M. A. Al-Jawary, Reliable iterative methods for mathematical model of COVID-19 based on data in Anhui, China, Commun. Math. Biol. Neurosci. 2020 (2020), 50. https://doi.org/10.28919/cmbn/4802

BibTeX
@article{Abed2020,
  author  = {Abed, Sawsan Mohsin and Al-Jawary, M.A.},
  title   = {Reliable iterative methods for mathematical model of COVID-19 based on data in Anhui, China},
  journal = {Commun. Math. Biol. Neurosci.},
  volume  = {2020},
  year    = {2020},
  pages   = {50},
  doi     = {10.28919/cmbn/4802}
}