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Fractional Stochastic Differential Equations -  Seda Igret Araz,  Abdon Atangana

Fractional Stochastic Differential Equations (eBook)

Applications to Covid-19 Modeling
eBook Download: PDF
2022 | 1. Auflage
XV, 540 Seiten
Springer Nature Singapore (Verlag)
978-981-19-0729-6 (ISBN)
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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.

ABDON ATANGANA is Professor of Applied Mathematics at the University of the Free State (UFS), Bloemfontein, Republic of South Africa. He obtained his honours and master degrees from the Department of Applied Mathematics at the UFS with distinction. He obtained his Ph.D. in applied mathematics from the Institute for Groundwater Studies, UFS, Republic of South Africa. He serves as Editor of many international journals, Guest Editor of many journals, and is a reviewer of more than 200 international accredited journals. He has published more than 270 research papers in international accredited journals of applied mathematics, applied physics, geo-hydrology and biomathematics. A single author of four books, including Numerical Methods for Fractional Differentiation (Springer, 2019), he has graduated 7 Ph.D. and 22 graduate students and 6 postdoc fellows. His research interests are in methods and applications of partial and ordinary differential equations, fractional differential equations, perturbation methods, asymptotic methods, iterative methods, and groundwater modelling. Professor Atangana is the founder of 'fractional calculus' with non-local and non-singular kernels popular in applied mathematics. A highly cited mathematician in 2019, 2020, 2021, he is the first-ever TWAS-Mohammad A award 2020 and Fellow of the World Academia of Science.
 
SEDA IGRET ARAZ is Assistant Professor of Mathematics at Siirt University, Siirt, Turkey. She obtained her master and Ph.D. degrees from Ataturk University, Turkey. She is the author of more than 27 papers published in top-tier journals and a book, New Numerical Scheme with Newton Polynomial: Theory, Methods, and Applications, co-authored by Prof. Abdon Atangana. She has acted as guest editor on some special issues in several journals.

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.
Erscheint lt. Verlag 22.4.2022
Reihe/Serie Industrial and Applied Mathematics
Zusatzinfo XV, 540 p. 162 illus. in color.
Sprache englisch
Themenwelt Mathematik / Informatik Mathematik Analysis
Mathematik / Informatik Mathematik Angewandte Mathematik
Mathematik / Informatik Mathematik Statistik
Mathematik / Informatik Mathematik Wahrscheinlichkeit / Kombinatorik
Schlagworte Applied mathematics • Biological Models • Covid-19 • Fractional Calculus • Fractional Differentiation • fractional integration • Numerical Methods • stochastic differential equation
ISBN-10 981-19-0729-3 / 9811907293
ISBN-13 978-981-19-0729-6 / 9789811907296
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