摘要
目的:分析ARIMA模型和指数平滑法对我国新型冠状肺炎(COVID-19)疫情变化趋势的预测效能。方法:选取我国2020年1月10日-2020年4月20日新冠肺炎累计确诊病例数作为ARIMA模型和指数平滑法的建模部分,2020年4月21日-2020年4月30日数据作为模型验证部分,比较两种模型的拟合情况和预测效果优劣。结果:ARIMA(2,2,1)模型的均方误差根(RMSE)为301.9043,相对误差百分比(REP)为3.1743,指数平滑模型的RMSE为200.9823,REP为2.1306。结论:指数平滑模型拟合效果较好,预测精度更高,可应用于我国COVID-19累计确诊病例数的预测。
Objective:To analyze the predictive power of the ARIMA model and exponential smoothing method for the trend of COVID-19 in China.Methods:The cumulative number of newly diagnosed cases of new coronary pneumonia in China from January 10,2020 to April 20,2020 was selected as the modeling part of the ARIMA model and exponential smoothing method,and the data from April 21,2020 to April 30,2020 was used as the model In the verification part,compare the fitting situation of the two models and the pros and cons of the prediction effect.Results:The root mean square error(RMSE)of the ARIMA(2,2,1)model was 301.9043,the relative error percentage(REP)was 3.1743,the RMSE of the exponential smoothing model was 200.9823,and the REP was 2.1306.Conclusion:The exponential smoothing model has a better fitting effect and higher prediction accuracy,and can be used to predict the cumulative number of confirmed cases of COVID-19 in China.
作者
卢普庆
LU Pu-qing(School of Economics,Anhui University,Hefei 230601,China)
出处
《价值工程》
2020年第23期164-167,共4页
Value Engineering
