DSpace Repository

New fuzzy fractional epidemic model involving death population

Show simple item record

dc.contributor.author Dhandapani, Prasantha Bharathi
dc.contributor.author Baleanu, Dumitru
dc.contributor.author Thippan, Jayakumar
dc.contributor.author Sivakumar, Vinoth
dc.date.accessioned 2022-07-07T11:45:42Z
dc.date.available 2022-07-07T11:45:42Z
dc.date.issued 2021
dc.identifier.citation Dhandapani, Prasantha Bharathi...et al. (2021). "New fuzzy fractional epidemic model involving death population", Computer Systems Science and Engineering, Vol. 37, No. 3, pp. 331-346. tr_TR
dc.identifier.issn 0267-6192
dc.identifier.uri http://hdl.handle.net/20.500.12416/5720
dc.description.abstract In this research, we propose a new change in classical epidemic models by including the change in the rate of death in the overall population. The existing models like Susceptible-Infected-Recovered (SIR) and Susceptible-Infected-Recovered-Susceptible (SIRS) include the death rate as one of the parameters to estimate the change in susceptible, infected and recovered populations. Actually, because of the deficiencies in immunity, even the ordinary flu could cause death. If people's disease resistance is strong, then serious diseases may not result in mortalities. The classical model always assumes a closed system where there is no new birth or death, no immigration or emigration, while in reality, such assumptions are not realistic. Moreover, the classical epidemic model does not report the change in population due to death caused by a disease. With this study, we try to incorporate the rate of change in the population of death caused by a disease, where the model is framed to reduce the curve of death along with the susceptible and infected populations. Since the rate of change turned out to be very small, we have tried to estimate it fractionally. Thus, the model is defined using fuzzy logic and is solved by two different methods: a Laplace Adomian decomposition method (LADM) and a differential transform method (DTM) for an arbitrary order α. To test its accuracy, we compared the results of both DTM and LADM with the fourth-order Runge-Kutta method (RKM-4) at α = 1. © 2021 CRL Publishing. All rights reserved. tr_TR
dc.language.iso eng tr_TR
dc.relation.isversionof 10.32604/CSSE.2021.015619 tr_TR
dc.rights info:eu-repo/semantics/closedAccess tr_TR
dc.subject Differential Transformation Method tr_TR
dc.subject Epidemic Model tr_TR
dc.subject Fourth-Order tr_TR
dc.subject Fractional-Order tr_TR
dc.subject Laplace Adomian Decomposition Method tr_TR
dc.subject Runge-Kutta Method tr_TR
dc.subject Susceptible-Infected-Recovered-Dead tr_TR
dc.title New fuzzy fractional epidemic model involving death population tr_TR
dc.type article tr_TR
dc.relation.journal Computer Systems Science and Engineering tr_TR
dc.contributor.authorID 56389 tr_TR
dc.identifier.volume 37 tr_TR
dc.identifier.issue 3 tr_TR
dc.identifier.startpage 331 tr_TR
dc.identifier.endpage 346 tr_TR
dc.contributor.department Çankaya Üniversitesi, Fen - Edebiyat Fakültesi, Matematik Bölümü tr_TR


Files in this item

Files Size Format View

There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record