通过两种不同的分数导数分析Covid-19的流行动态

IF 0.9 Q3 COMPUTER SCIENCE, THEORY & METHODS International Journal of Modeling Simulation and Scientific Computing Pub Date : 2022-05-08 DOI:10.1142/s1793962323500071
Pushpendra Kumar, V. S. Erturk, V. Govindaraj, M. Inc., H. Abboubakar, K. Nisar
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引用次数: 2

摘要

2019年12月,新型冠状病毒,也被称为2019- ncov或SARS-CoV-2或COVID-19,首次在中国武汉被确认为致命疾病。本文分析了两种不同的非经典冠状病毒模型来观察该疾病的爆发。考虑用卡普托和卡普托-法布里齐奥(C-F)分数阶导数用两种不同的方法来模拟给定的流行病模型。我们在实际数据的帮助下进行了所有需要的图形模拟,以演示所提出系统的行为。我们观察到,所给出的方案是非常有效的,适合于分析冠状病毒的动力学。我们发现给定的模型类在Caputo和C-F导数意义下具有不同的性质。本研究的主要贡献是提出了一种新的建模框架,以显示分数阶解如何比整数阶算子更清楚地描述疾病动力学。使用Caputo(奇点型核)和Caputo- fabrizio(指数衰减型核)两种不同的分数阶导数的动机是探索不同核下的模型动力学。两种不同核性质在同一模型上的应用,使本研究更有效地用于科学观测。©2023世界科学出版公司。
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Dynamics of Covid-19 epidemic via two different fractional derivatives
In December 2019, the novel Coronavirus, also known as 2019-nCoV or SARS-CoV-2 or COVID-19, was first recognized as a deadly disease in Wuhan, China. In this paper, we analyze two different nonclassical Coronavirus models to observe the outbreaks of this disease. Caputo and Caputo-Fabrizio (C-F) fractional derivatives are considered to simulate the given epidemic models by using two separate methods. We perform all required graphical simulations with the help of real data to demonstrate the behavior of the proposed systems. We observe that the given schemes are highly effective and suitable to analyze the dynamics of Coronavirus. We find different natures of the given model classes for both Caputo and C-F derivative sense. The main contribution of this study is to propose a novel framework of modeling to show how the fractional-order solutions can describe disease dynamics much more clearly as compared to integer-order operators. The motivation to use two different fractional derivatives, Caputo (singular-type kernel) and Caputo-Fabrizio (exponential decay-type kernel) is to explore the model dynamics under different kernels. The applications of two various kernel properties on the same model make this study more effective for scientific observations. © 2023 World Scientific Publishing Company.
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CiteScore
2.50
自引率
16.70%
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