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Fractional analysis of dynamical novel COVID-19 by semi-analytical technique

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dc.contributor.author Iqbal, S.
dc.contributor.author Baleanu, Dumitru
dc.contributor.author Ali, Javaid
dc.contributor.author Younas, H.M.
dc.contributor.author Riaz, M.B.
dc.date.accessioned 2022-04-29T12:58:54Z
dc.date.available 2022-04-29T12:58:54Z
dc.date.issued 2021
dc.identifier.citation Iqbal, S...et al. (2021). "Fractional analysis of dynamical novel COVID-19 by semi-analytical technique", CMES - Computer Modeling in Engineering and Science, Vol. 129, No. 2, pp. 705-727. tr_TR
dc.identifier.issn 1526-1492
dc.identifier.uri http://hdl.handle.net/20.500.12416/5478
dc.description.abstract This study employs a semi-analytical approach, called Optimal Homotopy Asymptotic Method (OHAM), to analyze a coronavirus (COVID-19) transmission model of fractional order. The proposed method employs Caputo's fractional derivatives and Reimann-Liouville fractional integral sense to solve the underlying model. To the best of our knowledge, this work presents the first application of an optimal homotopy asymptotic scheme for better estimation of the future dynamics of the COVID-19 pandemic. Our proposed fractional-order scheme for the parameterized model is based on the available number of infected cases from January 21 to January 28, 2020, in Wuhan City of China. For the considered real-time data, the basic reproduction number is R0 ≈ 2.48293 that is quite high. The proposed fractional-order scheme for solving the COVID-19 fractional-order model possesses some salient features like producing closed-form semi-analytical solutions, fast convergence and non-dependence on the discretization of the domain. Several graphical presentations have demonstrated the dynamical behaviors of subpopulations involved in the underlying fractional COVID-19 model. The successful application of the scheme presented in this work reveals new horizons of its application to several other fractional-order epidemiological models. © 2021 Tech Science Press. All rights reserved. tr_TR
dc.language.iso eng tr_TR
dc.relation.isversionof 10.32604/cmes.2021.015375 tr_TR
dc.rights info:eu-repo/semantics/openAccess tr_TR
dc.subject Fractional Analysis tr_TR
dc.subject Novel COVID-19 tr_TR
dc.subject Semi-Analytical Scheme tr_TR
dc.title Fractional analysis of dynamical novel COVID-19 by semi-analytical technique tr_TR
dc.type article tr_TR
dc.relation.journal CMES - Computer Modeling in Engineering and Sciences tr_TR
dc.contributor.authorID 56389 tr_TR
dc.identifier.volume 129 tr_TR
dc.identifier.issue 2 tr_TR
dc.identifier.startpage 705 tr_TR
dc.identifier.endpage 727 tr_TR
dc.contributor.department Çankaya Üniversitesi, Fen - Edebiyat Fakültesi, Matematik Bölümü tr_TR


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