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不同分数阶导数框架下埃博拉疾病的动力学

Dynamics of Ebola Disease in the Framework of Different Fractional Derivatives.

作者信息

Muhammad Altaf Khan, Atangana Abdon

机构信息

Department of Mathematics, City University of Science and Information Technology, Peshawar 25000, Pakistan.

Institute for Groundwater Studies, Faculty of Natural and Agricultural Sciences, University of the Free State, Bloemfontein 9300, South Africa.

出版信息

Entropy (Basel). 2019 Mar 21;21(3):303. doi: 10.3390/e21030303.

Abstract

In recent years the world has witnessed the arrival of deadly infectious diseases that have taken many lives across the globe. To fight back these diseases or control their spread, mankind relies on modeling and medicine to control, cure, and predict the behavior of such problems. In the case of Ebola, we observe spread that follows a fading memory process and also shows crossover behavior. Therefore, to capture this kind of spread one needs to use differential operators that posses crossover properties and fading memory. We analyze the Ebola disease model by considering three differential operators, that is the Caputo, Caputo-Fabrizio, and the Atangana-Baleanu operators. We present brief detail and some mathematical analysis for each operator applied to the Ebola model. We present a numerical approach for the solution of each operator. Further, numerical results for each operator with various values of the fractional order parameter α are presented. A comparison of the suggested operators on the Ebola disease model in the form of graphics is presented. We show that by decreasing the value of the fractional order parameter α , the number of individuals infected by Ebola decreases efficiently and conclude that for disease elimination, the Atangana-Baleanu operator is more useful than the other two.

摘要

近年来,世界目睹了致命传染病的出现,这些传染病在全球夺走了许多人的生命。为了抗击这些疾病或控制其传播,人类依靠建模和医学来控制、治愈并预测此类问题的行为。以埃博拉疫情为例,我们观察到其传播遵循衰减记忆过程,并且还表现出交叉行为。因此,为了捕捉这种传播情况,需要使用具有交叉特性和衰减记忆的微分算子。我们通过考虑三种微分算子,即卡普托(Caputo)算子、卡普托 - 法布里齐奥(Caputo - Fabrizio)算子和阿坦加纳 - 巴莱亚努(Atangana - Baleanu)算子,来分析埃博拉疾病模型。我们针对应用于埃博拉模型的每个算子给出简要细节和一些数学分析。我们给出了每个算子的数值求解方法。此外,还给出了分数阶参数α取不同值时每个算子的数值结果。以图形形式展示了所建议的算子在埃博拉疾病模型上的比较情况。我们表明,通过降低分数阶参数α的值,感染埃博拉的人数会有效减少,并得出结论,对于消除疾病而言,阿坦加纳 - 巴莱亚努算子比其他两个算子更有用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c1f2/7514785/253194620ba1/entropy-21-00303-g001.jpg

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