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Title:: Analysis of COVID-19 in Hubei province based on machine learning and dynamics model

作者:: 余锦芬1; 宋玉凯2△; 费菲1; 孙卫强1; 宋祖峰3; 1.华中科技大学同济医学院附属湖北妇幼保健院，武汉 430070；2.电子科技大学格拉斯哥学院，成都 611731；3.中冶南方工程技术有限公司，武汉 430223

Author(s):: YU Jinfen1; SONG Yukai2; FEI Fei1; SUN Weiqiang1; SONG Zufeng3; 1.Maternal and Child Hospital of Hubei Province, Tongji Medical College, Huazhong University of Science and Technology，Wuhan 430070，China;2.Glasgow College,UESTC,Chengdu 611731,China;3. WISDRI Engineering ＆ Research Incorporation Limited,Wuhan 430223

Keywords:: Machine learning; SIR model; SIER model; Cellular automata model; COVID-19

摘要:: 基于武昌方舱医院的一线数据和其他官方数据，我们首先利用机器学习对疫情规模进行预测，之后利用回溯传播模型和抽样检测模型对疫情规模进行估计，最后从宏观角度上用SIR和SIER模型结合MATLAB软件编程对疫情进行分析，采用元胞自动机模型在微观角度上的分析，从两个角度证明了中国政府强有力的防控措施的必要性。

Abstract:: Based on the data of the Wuchang mobile cabin hospital and other official data, we firstly used machine learning to predict the scale of the outbreak, and then adapted the trace transmission model and the sampling detection model to estimate the scale of the outbreak. Finally, SIR and SIER models were used in combination with MATLAB software programming to analyze the epidemic situation from the macro perspective, the cellular automata model was used in the micro perspective for simulation.It proves the necessity of the Chinese government′s strong prevention and control measures from two perspectives.