Numerical solutions and simulations of the fractional COVID-19 model via Pell–Lucas collocation algorithm

IF 2.1 3区数学 Q1 MATHEMATICS, APPLIED

Mathematical Methods in the Applied Sciences Pub Date : 2024-07-31 DOI:10.1002/mma.10284

Gamze Yıldırım, Şuayip Yüzbaşı

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引用次数: 0

Abstract

The aim of this study is to present the evolution of COVID-19 pandemic in Turkey. For this, the SIR (Susceptible, Infected, Removed) model with the fractional order derivative is employed. By applying the collocation method via the Pell–Lucas polynomials (PLPs) to this model, the approximate solutions of model with fractional order derivative are obtained. Hence, the comments are made about the susceptible population, the infected population, and the recovered population. For the method, firstly, PLPs are expressed in matrix form for a selected number of $N$ . With the help of this matrix relationship, the matrix forms of each term in the SIR model with the fractional order derivative are constituted. For implementation and visualization, we utilize MATLAB. Moreover, the outcomes for the Runge–Kutta method (RKM) are obtained using MATLAB, and these results are compared with the results obtained with the Pell–Lucas collocation method (PLCM). From all simulations, it is concluded that the presented method is effective and reliable.

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通过 Pell-Lucas 配位算法对分数 COVID-19 模型进行数值求解和模拟

本研究旨在介绍 COVID-19 大流行病在土耳其的演变情况。为此，我们采用了具有分数阶导数的 SIR（易感、感染、清除）模型。通过对该模型应用佩尔-卢卡斯多项式（PLPs）的配位法，得到了分数阶导数模型的近似解。因此，对易感人群、感染人群和康复人群进行了评论。在该方法中，首先将选定数量的 PLPs 用矩阵形式表示出来。借助这种矩阵关系，可以构成带分数阶导数的 SIR 模型中每项的矩阵形式。为了实现和可视化，我们使用了 MATLAB。此外，我们还利用 MATLAB 获得了 Runge-Kutta 方法（RKM）的结果，并将这些结果与 Pell-Lucas 置位法（PLCM）的结果进行了比较。从所有模拟中得出的结论是，所提出的方法是有效和可靠的。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Mathematical Methods in the Applied Sciences 数学-应用数学

CiteScore

4.90

自引率

6.90%

发文量

798

审稿时长

6 months

期刊介绍： Mathematical Methods in the Applied Sciences publishes papers dealing with new mathematical methods for the consideration of linear and non-linear, direct and inverse problems for physical relevant processes over time- and space- varying media under certain initial, boundary, transition conditions etc. Papers dealing with biomathematical content, population dynamics and network problems are most welcome. Mathematical Methods in the Applied Sciences is an interdisciplinary journal: therefore, all manuscripts must be written to be accessible to a broad scientific but mathematically advanced audience. All papers must contain carefully written introduction and conclusion sections, which should include a clear exposition of the underlying scientific problem, a summary of the mathematical results and the tools used in deriving the results. Furthermore, the scientific importance of the manuscript and its conclusions should be made clear. Papers dealing with numerical processes or which contain only the application of well established methods will not be accepted. Because of the broad scope of the journal, authors should minimize the use of technical jargon from their subfield in order to increase the accessibility of their paper and appeal to a wider readership. If technical terms are necessary, authors should define them clearly so that the main ideas are understandable also to readers not working in the same subfield.