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Modeling of anthrax disease via efficient computing techniques

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dc.contributor.author Raza, Ali
dc.contributor.author Baleanu, Dumitru
dc.contributor.author Yousaf, Muhammad
dc.contributor.author Akhter, Naeem
dc.contributor.author Mahmood, Syed Kashif
dc.contributor.author Rafiq, Muhammad
dc.date.accessioned 2022-06-17T12:18:49Z
dc.date.available 2022-06-17T12:18:49Z
dc.date.issued 2022
dc.identifier.citation Raza, Ali...et al. (2022). "Modeling of anthrax disease via efficient computing techniques", Intelligent Automation and Soft Computing, Vol. 32, No. 2, pp. 1109-1124. tr_TR
dc.identifier.issn 1079-8587
dc.identifier.uri http://hdl.handle.net/20.500.12416/5671
dc.description.abstract Computer methods have a significant role in the scientific literature. Nowadays, development in computational methods for solving highly complex and nonlinear systems is a hot issue in different disciplines like engineering, physics, biology, and many more. Anthrax is primarily a zoonotic disease in herbivores caused by a bacterium called Bacillus anthracis. Humans generally acquire the disease directly or indirectly from infected animals, or through occupational exposure to infected or contaminated animal products. The outbreak of human anthrax is reported in the Eastern Mediterranean regions like Pakistan, Iran, Iraq, Afghanistan, Morocco, and Sudan. Almost ninety-five percent chances are the transmission of the bacteria from forming spores by the World Health Organization (WHO). The modeling of an anthrax disease is based on the four compartments along with two humans (susceptible and infected) and others are dead bodies and sporing agents. The mathematical analysis is studied along with the fundamental properties of deterministic modeling. The stability of the model along with equilibria is studied rigorously. The authentication of analytical results is examined through well-known computer methods like Euler, Runge Kutta, and Non-standard finite difference (NSFD) along with the feasible properties (positivity, boundedness, and dynamical consistency) of the model. In the end, comparison analysis of algorithms shows the effectiveness of the methods. © 2022, Tech Science Press. All rights reserved. tr_TR
dc.language.iso eng tr_TR
dc.relation.isversionof 10.32604/iasc.2022.022643 tr_TR
dc.rights info:eu-repo/semantics/openAccess tr_TR
dc.subject Anthrax Disease tr_TR
dc.subject Computer Methods tr_TR
dc.subject Deterministic Modeling tr_TR
dc.subject Stability Analysis tr_TR
dc.title Modeling of anthrax disease via efficient computing techniques tr_TR
dc.type article tr_TR
dc.relation.journal Intelligent Automation and Soft Computing tr_TR
dc.contributor.authorID 56389 tr_TR
dc.identifier.volume 32 tr_TR
dc.identifier.issue 2 tr_TR
dc.identifier.startpage 1109 tr_TR
dc.identifier.endpage 1124 tr_TR
dc.contributor.department Çankaya Üniversitesi, Fen - Edebiyat Fakültesi, Matematik Bölümü tr_TR


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