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通过新型广义卡普托型分数阶导数对印度新冠疫情的案例研究

A case study of Covid-19 epidemic in India via new generalised Caputo type fractional derivatives.

作者信息

Kumar Pushpendra, Suat Erturk Vedat

机构信息

Department of Mathematics and Statistics, School of Basic and Applied Sciences Central University of Punjab Bathinda 151001 Punjab India.

Department of Mathematics Ondokuz Mayis University Samsun 55200 Atakum Turkey.

出版信息

Math Methods Appl Sci. 2021 Feb 17. doi: 10.1002/mma.7284.

Abstract

The first symptomatic infected individuals of coronavirus (Covid-19) was confirmed in December 2020 in the city of Wuhan, China. In India, the first reported case of Covid-19 was confirmed on 30 January 2020. Today, coronavirus has been spread out all over the world. In this manuscript, we studied the coronavirus epidemic model with a true data of India by using Predictor-Corrector scheme. For the proposed model of Covid-19, the numerical and graphical simulations are performed in a framework of the new generalised Caputo sense non-integer order derivative. We analysed the existence and uniqueness of solution of the given fractional model by the definition of Chebyshev norm, Banach space, Schauder's second fixed point theorem, Arzel's-Ascoli theorem, uniform boundedness, equicontinuity and Weissinger's fixed point theorem. A new analysis of the given model with the true data is given to analyse the dynamics of the model in fractional sense. Graphical simulations show the structure of the given classes of the non-linear model with respect to the time variable. We investigated that the mentioned method is copiously strong and smooth to implement on the systems of non-linear fractional differential equation systems. The stability results for the projected algorithm is also performed with the applications of some important lemmas. The present study gives the applicability of this new generalised version of Caputo type non-integer operator in mathematical epidemiology. We compared that the fractional order results are more credible to the integer order results.

摘要

2020年12月,中国武汉市确诊了首例有症状的新型冠状病毒(Covid-19)感染病例。在印度,首例Covid-19报告病例于2020年1月30日得到确认。如今,冠状病毒已在全球蔓延。在本手稿中,我们使用预估-校正格式,利用印度的真实数据研究了冠状病毒流行模型。对于所提出的Covid-19模型,在新的广义Caputo意义下的非整数阶导数框架内进行了数值和图形模拟。我们通过切比雪夫范数的定义、巴拿赫空间、绍德尔第二不动点定理、阿尔泽拉-阿斯科利定理、一致有界性、等度连续性和魏辛格不动点定理,分析了给定分数阶模型解的存在性和唯一性。对给定模型与真实数据进行了新的分析,以分析该模型在分数阶意义下的动态。图形模拟展示了给定类别的非线性模型相对于时间变量的结构。我们研究发现,所提及的方法在非线性分数阶微分方程系统上实施起来非常强大且流畅。还应用了一些重要引理对所提出算法的稳定性结果进行了分析。本研究给出了这种新的广义Caputo型非整数算子在数学流行病学中的适用性。我们比较得出,分数阶结果比整数阶结果更可靠。

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