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Evolutionary computational method for tuberculosis model with fuzziness

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dc.contributor.author Alsaadi, Ateq
dc.contributor.author Dayan, Fazal
dc.contributor.author Ahmed, Nauman
dc.contributor.author Baleanu, Dumitru
dc.contributor.author Rafiq, Muhammad
dc.contributor.author Raza, Ali
dc.date.accessioned 2023-12-07T12:31:22Z
dc.date.available 2023-12-07T12:31:22Z
dc.date.issued 2023-08-01
dc.identifier.citation Alsaadi, Ateq...et.al. (2023). "Evolutionary computational method for tuberculosis model with fuzziness", AIP Advances, Vol.13, No.8. tr_TR
dc.identifier.issn 2158-3226
dc.identifier.uri http://hdl.handle.net/20.500.12416/6767
dc.description.abstract This work investigates the computational study of a six-compartmental mathematical model of tuberculosis disease dynamics with the impact of vaccination. Traditional mathematical models presume that all variables are precise and can be measured or calculated precisely. However, in many real-world scenarios, variables may need to be more accurate or easier to quantify, resulting in model uncertainty. Considering this, fuzziness is introduced into the model by taking the contact, recovery, and death rates due to disease as fuzzy membership functions. Two numerical computational schemes, forward Euler and nonstandard finite difference (NSFD), are designed to solve the model. The positivity and convergence for the developed method are investigated, which are significant characteristics of these dynamical models, and it is revealed that these features are preserved in the extended scheme. Numerical computations are performed to support the analytical results. The numerical and computational results indicate that the proposed NSFD method adequately represents the dynamics of the disease despite the uncertainty and heterogeneity. Moreover, the obtained method generates plausible predictions that regulators can use to design and develop control strategies to support decision-making tr_TR
dc.language.iso eng tr_TR
dc.relation.isversionof 10.1063/5.0165348 tr_TR
dc.rights info:eu-repo/semantics/openAccess tr_TR
dc.subject Computational Methods tr_TR
dc.subject Computer Simulation tr_TR
dc.subject Mathematical Modeling tr_TR
dc.subject Numerical Differentiation tr_TR
dc.subject Fuzzy Numbers tr_TR
dc.subject Diseases And Conditions tr_TR
dc.subject Organs tr_TR
dc.subject Bacteria tr_TR
dc.subject Epidemiology tr_TR
dc.subject Immune System tr_TR
dc.title Evolutionary computational method for tuberculosis model with fuzziness tr_TR
dc.type article tr_TR
dc.relation.journal AIP Advances tr_TR
dc.contributor.authorID 56389 tr_TR
dc.identifier.volume 13 tr_TR
dc.identifier.issue 8 tr_TR
dc.contributor.department Çankaya Üniversitesi, Fen - Edebiyat Fakültesi, Matematik Bölümü tr_TR


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