弥合基于普通方程,延迟方程和分数方程的模型之间的差距,通过整数内核来弥合差距
Noemi Zeraick Monteiro1, Rodrigo Weber Dos Santos1, Sandro Rodrigues Mazorche2
1Graduate Program in Computational Modeling, Federal University of Juiz de Fora, Juiz de Fora, Minas Gerais 36036-900, Brazil.
概括
这项研究统一了古典,延迟和分数模型,使用玛米塔格-莱弗勒内核来计算进化方程. 该框架结合了历史数据,增强了COVID-19动态等系统的数学建模.
科学领域:
- 数学生物学 数学生物学
- 动态系统 动态系统
- 分数微积分的计算.
背景情况:
- 用卷积运算符建立了进化方程,但在将特定内核与高级模型联系起来方面存在差距.
- 经典,延迟和分数微分方程往往孤立存在,缺乏统一的理论框架.
研究的目的:
- 开发一个统一的框架,用于演化方程使用一般的卷积内核.
- 证明经典,延迟和分数模型是该框架的特殊情况.
- 分析概括模型的属性和应用,包括其纳入历史数据的能力.
主要方法:
- 利用一个gamma Mittag-Leffler内存内核来概括进化方程.
- 分类了不同的内核类型,并分析了一般模型的非对称行为.
- 进行了数值模拟和参数分析,用于内核分类.
主要成果:
- 建立了一个统一的框架,包括经典,延迟和分数模型.
- 构建的分数模型保持维度平衡,并明确将分数顺序与过去的数据联系起来.
- 证明了该模型在澳大利亚,巴西和秘鲁复制COVID-19感染动态的能力.
结论:
- 拟议的统一框架有效地通过整微分方程将历史数据纳入.
- 这种方法扩展了普通,延迟或分数微分方程描述的系统的数学建模能力.
- 玛Mittag-Leffler内核提供了一个多功能工具,用于模拟复杂的动态与内存效应.
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