大气和海洋科学快报（英文版）2021，Vol.14Issue(4)：58-62,5.
新冠肺炎流行病学模型的最优参数化
Optimal parameterization of COVID-19 epidemic models
摘要
Abstract
At the time of writing,coronavirus disease 2019(COVID-19)is seriously threatening human lives and health throughout the world.Many epidemic models have been developed to provide references for decision-making by governments and the World Health Organization.To capture and understand the characteristics of the epidemic trend,parameter optimization algorithms are needed to obtain model parameters.In this study,the authors pro-pose using the Levenberg-Marquardt algorithm(LMA)to identify epidemic models.This algorithm combines the advantage of the Gauss-Newton method and gradient descent method and has improved the stability of parame-ters.The authors selected four countries with relatively high numbers of confirmed cases to verify the advantages of the Levenberg-Marquardt algorithm over the traditional epidemiological model method.The results show that the Statistical-SIR(Statistical-Susceptible-Infected-Recovered)model using LMA can fit the actual curve of the epidemic well,while the epidemic simulation of the traditional model evolves too fast and the peak value is too high to reflect the real situation.关键词
新冠肺炎/统计方法/Levenberg-Marquardt算法/SIR模型Key words
COVID-19/Statistical method/Levenberg-Marquardt algorithm/SIR model引用本文复制引用
Li Zhang,Jianping Huang,Haipeng Yu,Xiaoyue Liu,Yun Wei,Xinbo Lian,Chuwei Liu,Zhikun Jing..新冠肺炎流行病学模型的最优参数化[J].大气和海洋科学快报（英文版）,2021,14(4):58-62,5.基金项目
This work was jointly supported by the National Natural Science Foundation of China[grant number 41521004]and the Gansu Provin-cial Special Fund Project for Guiding Scientific and Technological Inno-vation and Development[grant number 2019ZX-06]. （）
