New techniques to estimate the solution of autonomous system

Mahdi A. Sabea, Maha A. Mohammed


This research aims to solve the nonlinear model formulated in a system of differential equations with an initial value problem (IVP) represented in COVID-19 mathematical epidemiology model as an application using new approach: Approximate Shrunken are proposed to solve such model under investigation, which combines classic numerical method and numerical simulation techniques in an effective statistical form which is shrunken estimation formula. Two numerical simulation methods are used firstly to solve this model: Mean Monte Carlo Runge-Kutta and Mean Latin Hypercube Runge-Kutta Methods. Then two approximate simulation methods are proposed to solve the current study. The results of the proposed approximate shrunken methods and the numerical simulation methods are compared with the standard results of the numerical method which is Runge-Kutta 4th Method from the year 2021 to 2025, using the absolute error, through comparison, it becomes clear that the approximate proposed solution is better and closer to the standard solution than the solutions of other methods that used to solve this system. The results are tabulated and represented graphically, as well as a discussion to prove the efficiency of the proposed methods.

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Published: 2023-08-21

How to Cite this Article:

Mahdi A. Sabea, Maha A. Mohammed, New techniques to estimate the solution of autonomous system, Commun. Math. Biol. Neurosci., 2023 (2023), Article ID 87

Copyright © 2023 Mahdi A. Sabea, Maha A. Mohammed. 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.

Commun. Math. Biol. Neurosci.

ISSN 2052-2541

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