对随机人口模型的随机时间转移分布的计算
Dylan Morris1, John Maclean2, Andrew J Black2
1School of Computer and Mathematical Sciences, The University of Adelaide, Adelaide, SA, 5005, Australia. dylan.morris@adelaide.edu.au.
Journal of mathematical biology
|August 12, 2024
概括
来自小的初始群体的噪声效应在大型系统中持续存在. 一种新的数值方法使用随机时间转移有效地近似这些效应,避免了对人口模型进行昂贵的模拟.
科学领域:
- 数学生物学的数学生物学
- 计算建模计算建模
- 随机过程是指随机的过程.
背景情况:
- 确定性模型无法捕捉大系统中小初始群体的噪声效应.
- 这些早期的噪音效应可以对宏观行为产生持续的,可测量的影响.
- 接近这些影响需要考虑初始条件的变化.
研究的目的:
- 开发一种高效的数值方法,用于计算随机人口模型中的时移分布.
- 为了提供一个实用的工具,在没有广泛的模拟的情况下生成宏观轨迹.
- 证明该方法在流行病和病毒动态模型上的适用性.
主要方法:
- 开发基于微分函数方程的数值方法.
- 通过推导模型速率规则来自动计算时间转移分布.
- 将该方法应用于质量作用混合模型.
主要成果:
- 开发了一种计算时移分布的高效方法.
- 该方法准确地接近在大型随机系统中的持续噪声效应.
- 这种方法避免了传统随机模拟的计算费用.
结论:
- 新的数值方法有效地捕捉了随机人口动态中的持续噪声效应.
- 这种方法为直接随机模拟提供了一个计算效率高的替代方案.
- 该方法广泛适用于各种人口模型,包括流行病学和病毒学模型.
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