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一种与冠状病毒优化算法的新型聚合方法,用于最佳控制COVID-19:中国武汉的一个案例研究

Raheleh Khanduzi¹, Amin Jajarmi², Asiyeh Ebrahimzadeh³

¹Department of Mathematics and Statistics, Gonbad Kavous University, P.O. Box, 49717-99151, Gonbad Kavous, Iran.

Computers in biology and medicine

|June 6, 2024

概括

本研究介绍了一种使用Legendre波段和一种新的COVIDOA算法进行数值优化方法,以找到最佳的COVID-19控制策略. 结果显示,快速检测和最大限度地减少环境病毒传播显著减少传播.

科学领域:

数学建模的数学建模
流行病学流行病学
计算科学计算科学

背景情况:

由于COVID-19的流行,需要采取有效的控制策略.
优化控制模式对于控制传染病传播至关重要.
了解传播动态是公共卫生干预的关键.

研究的目的:

开发一种数字优化方法,以最佳控制COVID-19的传播.
评估各种控制策略对减少暴露和传染个体的影响.
将一种新的优化算法应用于COVID-19传播模型.

主要方法:

利用了Legendre波段和它们的衍生运算矩阵.
采用了拼接方法,将最佳控制模型转换为非线性编程 (NLP) 问题.
应用了冠状病毒优化算法 (COVIDOA) 来解决NLP问题.

主要成果:

研究了三个控制计划:个人保护,快速检测,延迟治疗和环境病毒分散.
在中国针对COVID-19的SEIR类型模型中应用策略.
分析了各种参数对COVID-19传播动态的影响.

结论:

数字结果表明,尽量减少暴露和传染个体的重大影响.
专注于快速检测,管理治疗延迟和环境病毒扩散的战略是有效的.
开发的优化方法为控制和预防COVID-19传播提供了有价值的工具.

关键词:

在 COVID-19 疫情中,配合方法的配合方法.冠状病毒优化算法莱根德尔波形小组 (Legendre wavelet) 是一个波形小组.最佳的控制控制是最好的控制.这就是SEIR模型.

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