A delayed plant disease model with Caputo fractional derivatives.

IF 2.3 Q1 MATHEMATICS
Pushpendra Kumar, Dumitru Baleanu, Vedat Suat Erturk, Mustafa Inc, V Govindaraj
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Abstract

We analyze a time-delay Caputo-type fractional mathematical model containing the infection rate of Beddington-DeAngelis functional response to study the structure of a vector-borne plant epidemic. We prove the unique global solution existence for the given delay mathematical model by using fixed point results. We use the Adams-Bashforth-Moulton P-C algorithm for solving the given dynamical model. We give a number of graphical interpretations of the proposed solution. A number of novel results are demonstrated from the given practical and theoretical observations. By using 3-D plots we observe the variations in the flatness of our plots when the fractional order varies. The role of time delay on the proposed plant disease dynamics and the effects of infection rate in the population of susceptible and infectious classes are investigated. The main motivation of this research study is examining the dynamics of the vector-borne epidemic in the sense of fractional derivatives under memory effects. This study is an example of how the fractional derivatives are useful in plant epidemiology. The application of Caputo derivative with equal dimensionality includes the memory in the model, which is the main novelty of this study.

带有卡普托分数导数的延迟植物病害模型。
我们分析了一个包含贝丁顿-德安吉利斯函数反应感染率的时延卡普托型分数数学模型,以研究媒介传播植物流行病的结构。我们利用定点结果证明了给定延迟数学模型的唯一全局解存在性。我们使用 Adams-Bashforth-Moulton P-C 算法求解给定的动力学模型。我们对提出的解给出了一些图形解释。从给定的实践和理论观察中,我们展示了一些新的结果。通过使用三维图,我们观察到当分数阶数变化时,我们的图的平整度也会发生变化。我们还研究了时间延迟对所提出的植物病害动力学的作用,以及感染率对易感人群和感染人群的影响。这项研究的主要动机是考察记忆效应下分数导数意义上的病媒传染病动力学。本研究是分式导数在植物流行病学中的应用实例。等维度卡普托导数的应用包括模型中的记忆,这是本研究的主要创新之处。
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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CiteScore
2.30
自引率
0.00%
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