ARIMAX与多变量LSTM模型在盐城市总死亡人数预测中的比较研究  

Comparison of ARIMAX and multivariate LSTM model in predicting daily death toll in Yancheng City

作　　者：黄钰姝 宋和佳 张睿[2] 李永红[1] 黄连成[3] 程义斌[1] 姚孝元[1] HUANG Yushu;SONG Hejia;ZHANG Rui;LI Yonghong;HUANG Liancheng;CHENG Yibin;YAO Xiaoyuan(Natinal Institute of Environmental Health,Chinese Center for Disease Control and Prevention,Beijing 100021,China;Chinese Center for Disease Control and Prevention,Beijing 102206,China;Yancheng Center for Disease Control and Prevention,Yancheng,Jiangsu 224000,China)

机构地区：[1]中国疾病预防控制中心环境与健康相关产品安全所,北京100021 [2]中国疾病预防控制中心 [3]江苏省盐城市疾病预防控制中心

出　　处：《公共卫生与预防医学》2021年第5期6-10,共5页Journal of Public Health and Preventive Medicine

基　　金：国家科技基础资源调查专项(2017FY101201);国家科技重大专项(2017ZX10305501-009)。

摘　　要：目的探讨比较多元自回归移动平均模型(Autoregressive Integrated Moving Averagemodel-X,ARIMAX)与多变量长短期记忆神经网络(Long Short Term Memory Network,LSTM)模型在盐城市总死亡人数预测中的效果。方法采用2014年1月1日至2017年6月30日江苏省盐城市每日总死亡人数、气象因素和空气质量数据,建立ARIMAX及多变量LSTM模型,并对2017年7月1日至7月14日每日总死亡人数进行预测,以RMSE、MAE、MAPE为评价指标比较两种模型的预测效果。结果ARIMAX(4,1,1)模型和多变量LSTM模型的RMSE、MAE、MAPE值分别为20.742、15.094、9.921和47.182、35.863、19.633。结论ARIMAX模型比多变量LSTM模型更适于预测盐城市每日死亡人数。Objective To compare the effects of Autoregressive Integrated Moving Average model-X(ARIMAX)and multivariate Long Short Term Memory Network(multivariate LSTM)in the prediction of daily total death toll in Yancheng City.Methods Based on total death toll data,meteorological data and air quality data from January 1 st,2014 to June 30 th,2017 in Yancheng City,Jiangsu province,ARIMAX model and multivariate LSTM model were established to predict the daily total death toll from July 1 st,2017 to July 14 th,2017.RMSE,MAE and MAPE were used as evaluation indexes to compare the prediction effects of these two models.Results RMSE,MAE and MAPE of ARIMAX model and multivariate LSTM model were 20.742、15.094、9.921 and 47.182、35.863、19.633,respectively.Conclusion ARIMAX model is better than multivariate LSTM model to predict the daily death toll in Yancheng city.

关 键 词：ARIMAX LSTM 时间序列 预测 每日总死亡人数 

分 类 号：R195[医药卫生—卫生统计学] R512.6[医药卫生—卫生事业管理]