随机微分方程隐式milstein方法的数值模拟

Journal of Fundamental Mathematics and Applications (JFMA) Pub Date : 2020-06-10 DOI:10.14710/jfma.v3i1.7416

R. Herdiana

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摘要

刚性随机微分方程在包括生物学在内的许多领域都有应用。本文采用文献[6]中提出的改进的1阶隐式Milstein方法，给出了马尔萨斯种群模型和SIS流行病模型随机微分方程的数值解。采用开源编程语言SCILAB进行数值模拟。结果表明，与隐式欧拉方法相比，该方法具有更高的精度和稳定性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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NUMERICAL SIMULATION OF STOCHASTIC DIFFERENTIAL EQUATIONS USING IMPLICIT MILSTEIN METHOD

Stiff stochastic differential equations arise in many applications including in the area of biology. In this paper, we present numerical solution of stochastic differential equations representing the Malthus population model and SIS epidemic model, using the improved implicit Milstein method of order one proposed in [6]. The open source programming language SCILAB is used to perform the numerical simulations. Results show that the method is more accurate and stable compared to the implicit Euler method.

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Journal of Fundamental Mathematics and Applications (JFMA)

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