报告题目：Explicit-implicit method for Susceptible-Infected-Recovered model

报 告 人：胡耀忠

主 持 人：陈锋

时 间：2026 年 7 月 24 日星期五 上午 9：30

地 点：Zoom Meeting ID: 962 2381 2116 Passcode: 2026

主办单位：数学与统计学院

报告人简介： 胡耀忠教授师从国际著名概率学者 PaulAndre Meyer，于 1992 年在法国是斯特拉斯堡大学取得博士学位。现任加拿大阿尔贝塔大学数学系特聘和终身教授，美国数理统计学会会士。曾任美国 Kansas 大学助理教授、副教授和教授。长期访问过法国斯特拉斯堡大学，美国北卡罗莱纳大学教堂山分校，加州大学尔湾分校，挪威奥斯陆大学，德国鲁尔大学等。主要从事概率论和随机分析方面的研究。在 Annals ofProbability, Memoir of American Mathematical Society, Annals of AppliedProbability, Journal of FunctionalAnalysis，Transaction of American Mathematical Society 等概率论领域一流期刊发表论文 180 多篇。现为 Bernoulli,Acta Math Scientia, Stochastics 等杂志编委。

摘要： In this talk, I will present an explicit-implicit method to numerically solve the Susceptible-Infected-Recovered (SIR) model driven by Brownian motion. It is known that the components of solution of this system are positive and the sum is given by a known (random) quantity. Our scheme preserves the positivity and sums to a known random process property. The idea is to introduce a transformation to transform the SIR model into a differential system without the diffusion item. Then we apply an implicit numerical method to the newly obtained differential equation and show that the convergence order of our scheme is 1.0. The inverse transform will yield the convergence order 1.0 for the original SIR model. We confirm numerically our theoretical result by showing an example