使用利亚普诺夫稳定性分析的COVID-19模型的数值稳定性
1Department of Mathematics, SAS, Vellore Institute of Technology Chennai, Kellambakkam, Chennai, 600127, Tamilnadu, India.
Scientific reports
|February 5, 2026
概括
这项研究使用分数计算来建模COVID-19的动态,揭示了调整分数顺序可以加强记忆力,并可以防止混乱的疫情爆发,提供一种可靠和创新的方法来分析流行病.
科学领域:
- 流行病学 流行病学
- 数学生物学 数学生物学
- 分数微积分的计算.
背景情况:
- COVID-19 流行病呈现出复杂的,非线性动态.
- 传统的流行病学模型可能无法完全捕捉长期持久性和记忆效应.
研究的目的:
- 使用卡普托操作员开发和分析一个三维分数顺序的COVID-19模型.
- 调查模型的稳定性,独特性和混乱行为.
- 实施一个强大的数值方法来模拟流行病的动态.
主要方法:
- 制定一个由三个部分组成的小数顺序COVID-19模型 (A(t),B(t),C(t)).
- 卡普托衍生品的应用,以整合记忆效应.
- 使用Toufik-Atangana方法进行数值模拟.
- 对存在,独特性,平衡点和稳定性的分析.
- 包括分叉和混乱分析.
主要成果:
- 减少分数顺序可以增强记忆效果,并可以抑制混乱的爆发.
- 图菲克-阿坦加纳法为非线性分数系统提供了稳定而准确的解决方案.
- 该模型证明了稳定和不稳定动态的可靠捕获.
- 分叉分析为模型的行为和稳定性提供了洞察力.
结论:
- 分数计算为建模COVID-19动态提供了一个创新的和值得信赖的框架.
- 提出的模型和数值方法在计算上是高效和稳健的.
- 分数建模与稳定性和混乱分析的整合增强了对流行病行为的理解.
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