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Numerical Analysis of Stochastic Vector Borne Plant Disease Model

Kamaledin Abodayeh1, Ali Raza2, Muhammad Shoaib Arif2, *, Muhammad Rafiq3, Mairaj Bibi4, Rabia Fayyaz4

1 Department of Mathematics and General Sciences, Prince Sultan University, Riyadh, Saudi Arabia.
2 Stochastic Analysis & Optimization Research Group, Department of Mathematics, Air University, PAF Complex E-9, Islamabad, 44000, Pakistan.
3 Faculty of Engineering, University of Central Punjab, Bathinda, Lahore, Pakistan.
4 Department of Mathematics, Comsats University, Chak Shahzad Campus, Islamabad, Pakistan.

* Corresponding Author: Muhammad Shoaib Arif. Email: email.

Computers, Materials & Continua 2020, 63(1), 65-83. https://doi.org/10.32604/cmc.2020.08838

Abstract

We are associating the solutions of stochastic and deterministic vector borne plant disease model in this manuscript. The dynamics of plant model depends upon threshold number P. If P <1 then condition helpful to eradicate the disease in plants while P >1 explains the persistence of disease. Inappropriately, standard numerical systems do not behave well in certain scenarios. We have been proposed a structure preserving stochastic non-standard finite difference system to analyze the behavior of model. This system is dynamical consistent, positive and bounded as defined by Mickens.

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APA Style
Abodayeh, K., Raza, A., Arif, M.S., Rafiq, M., Bibi, M. et al. (2020). Numerical analysis of stochastic vector borne plant disease model. Computers, Materials & Continua, 63(1), 65-83. https://doi.org/10.32604/cmc.2020.08838
Vancouver Style
Abodayeh K, Raza A, Arif MS, Rafiq M, Bibi M, Fayyaz R. Numerical analysis of stochastic vector borne plant disease model. Comput Mater Contin. 2020;63(1):65-83 https://doi.org/10.32604/cmc.2020.08838
IEEE Style
K. Abodayeh, A. Raza, M.S. Arif, M. Rafiq, M. Bibi, and R. Fayyaz, “Numerical Analysis of Stochastic Vector Borne Plant Disease Model,” Comput. Mater. Contin., vol. 63, no. 1, pp. 65-83, 2020. https://doi.org/10.32604/cmc.2020.08838

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cc Copyright © 2020 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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