一种分数阶急性虫媒传染病模型的参数识别方法研究
Parameter Identification for a Fractional Dynamical Epidemic Model of Dengue Fever
摘要: 针对分数阶急性虫媒传染病模型系统参数识别问题，基于Gorenflo-Mainardi-Moretti-Paradisi (GMMP)格式和牛顿法，提出了一种求解分数阶急性虫媒传染病模型系统的数值方法。将改进的混合Nelder-Mead单纯形搜索和粒子群算法(PSO)运用到分数阶微分方程的分数阶和系数识别。仿真实验表明，获得的分数阶急性虫媒传染病模型系统比其他模型能提供更符合实际数据的数值结果。
Abstract: In order to solve the problem of parameter identification for a fractional dynamical epidemic model of dengue fever, a numerical technology is proposed based on the Gorenflo-Mainardi-Moretti- Para-disi (GMMP) formula and the Newton method in this paper. The improved algorithm (MH- NMSS-PSO) combining Nelder Mead simplex search and particle swarm optimization is applied to the fractional order and coefficient identification of the fractional differential equations. Simulation experiments show that the obtained fractional dengue fever model can provide better numerical results that agree very well with the real data.
文章引用：胡欣瑜, 罗金炎, 曾元琦, 陈静怡, 吴江淏. 一种分数阶急性虫媒传染病模型的参数识别方法研究[J]. 应用数学进展, 2023, 12(12): 5193-5201. https://doi.org/10.12677/AAM.2023.1212510

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