Fractional stochastic differential equations applications to COVID-19 modeling / [electronic resource] :

• 作者： Atangana, Abdon.
• 其他作者：
  • Igret Araz, Seda.
  • SpringerLink (Online service)
• 其他題名：
  • Industrial and applied mathematics.
• 出版： Singapore : Springer Nature Singapore :Imprint: Springer
• 叢書名： Industrial and applied mathematics,
• 主題： Stochastic differential equations. , Fractional differential equations. , COVID-19 (Disease)--Statistical methods. , Differential Equations. , Stochastic Calculus. , Operator Theory. , Applications of Mathematics. , Mathematical Modeling and Industrial Mathematics. , Numerical Analysis.
• ISBN： 9789811907296 (electronic bk.) 、 9789811907289 (paper)
• FIND@SFXID: CGU
• 資料類型: 電子書
• 內容註: History on Covid-19 Spread -- Fractional Di?erential and Integral Operators -- Existence and Uniqueness for stochastic di?erential equations -- Numerical scheme for a general Stochastic equation with classical and fractional derivatives -- A simple SIR model of Covid-19 spread -- An application of SEIRD approach -- Modelling the transmission of Coronavirus with SEIR approach -- Modeling the spread of Covid-19 with a SIA IR IU approach: Inclusion of unreported infected class -- A comprehensive analysis of Covid-19 model -- Analysis of SEIARD model of Coronavirus transmission -- A mathematical model with Covid-19 reservoir -- A new model with asymptomatic and quarantined classes.
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• 摘要註: This book provides a thorough conversation on the underpinnings of Covid-19 spread modelling by using stochastics nonlocal differential and integral operators with singular and non-singular kernels. The book presents the dynamic of Covid-19 spread behaviour worldwide. It is noticed that the spread dynamic followed process with nonlocal behaviours which resemble power law, fading memory, crossover and stochastic behaviours. Fractional stochastic differential equations are therefore used to model spread behaviours in different parts of the worlds. The content coverage includes brief history of Covid-19 spread worldwide from December 2019 to September 2021, followed by statistical analysis of collected data for infected, death and recovery classes.
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