Numerical Method of a Class of Stochastic Delay Population Models
Control Science and Engineering
Volume 2, Issue 1, June 2018, Pages: 27-35
Received: Dec. 1, 2018; Accepted: Dec. 19, 2018; Published: Jan. 14, 2019
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Authors
Changyou Wang, College of Automation, Chongqing University of Posts and Telecommunications, Chongqing, P. R. China; College of Applied Mathematics, Chengdu University of Information Technology, Chengdu, P. R. China
Kaixiang Yang, College of Automation, Chongqing University of Posts and Telecommunications, Chongqing, P. R. China
Xingcheng Pu, College of Automation, Chongqing University of Posts and Telecommunications, Chongqing, P. R. China
Rui Li, College of Automation, Chongqing University of Posts and Telecommunications, Chongqing, P. R. China
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Abstract
Our aim in this paper is to present the design and implementation of a new numerical method to solve a class of stochastic delay population models. Firstly, a stochastic predator-prey model with time-delay and white noise is established. And then, a numerical simulation method based on the Milstein method is proposed to simulate the stochastic population model. Finally, the numerical solutions of the population model are obtained by using MATLAB software. The simulation results show that the new numerical simulation method can truly reflect the persistence and extinction process of stochastic predator-prey model, and provide a reference for solving the numerical simulation of the similar population models.
Keywords
Time-Delay, White Noise, Stochastic Population Model, Numerical Simulation
To cite this article
Changyou Wang, Kaixiang Yang, Xingcheng Pu, Rui Li, Numerical Method of a Class of Stochastic Delay Population Models, Control Science and Engineering. Vol. 2, No. 1, 2018, pp. 27-35. doi: 10.11648/j.cse.20180201.13
Copyright
Copyright © 2018 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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