基于ARIMA的传染病流行趋势预测及防治对策

›› 2015, Vol. 28 ›› Issue (12): 48-.

基于ARIMA的传染病流行趋势预测及防治对策

桂腾叶,陈硕,隗立志,崔志军,周晓琳

(1.西藏大学工学院,西藏拉萨 850000;2.西藏大学藏文信息技术研究中心,西藏拉萨 850000)

出版日期:2015-12-15 发布日期:2015-12-15
作者简介:桂腾叶(1991—),男,本科。研究方向:交通运输规划与管理。E-mail:1148195268@qq.com
基金资助:
西藏大学自治区大学生创新性实验训练计划基金资助项目(2014QCX049)

Prediction and Countermeasures of Infectious Diseases Based on ARIMA

GUI Tengye,CHEN Shuo,WEI Lizhi,CUI Zhijun,ZHOU Xiaolin

(1.School of Engineering,University of Tibet,Lhasa 850000,China;
2.Tibetan Information Technology Research Center,University of Tibet,Lhasa 850000,China)

Online:2015-12-15 Published:2015-12-15

摘要/Abstract

摘要：

为准确地预测传染病,根据传染病变化特点,提出了一种差分自回归移动平均模型的传染病预测模型。模型对原始数据进行平稳化预处理,消除其突发性、季节性和周期性特征,并利用ARIMA对将平稳后的数据进行建模,采用某市流行性感冒发病率数据进行仿真,实验结果表明,ARIMA模型能较好地捕捉传染病变化规律,提高了预测精度,是一种有效预测传染病的方法,同时能为传染病的预防监测措施提供决策依据。

关键词: 传染病;平稳时间序列;预处理;ARIMA

Abstract:

An autoregressive integrated moving average model (ARIMA) based on the characteristics of infectious diseases changes is proposed for accurate prediction of the epidemics.Firstly,the original data is preprocessed smoothly by the model,which is also used to eliminate the abruptness and the characteristics of seasonal and cyclical.Then the ARIMA is used to build a model of data that has been smoothed.We use the data,the morbidity of influenza in a city,to simulate the results of the experiment,which shows that ARIMA can capture the regulation of the variation of infectious diseases well,and improve the accuracy of the prediction.It is an efficient approach to predicting the epidemic,which also provides support for decision-making in epidemic prediction and monitoring.

Key words: infectious disease;stationary time series;pretreatment;ARIMA

中图分类号:

O212

桂腾叶,陈硕,隗立志,崔志军,周晓琳. 基于ARIMA的传染病流行趋势预测及防治对策[J]. , 2015, 28(12): 48-.

GUI Tengye,CHEN Shuo,WEI Lizhi,CUI Zhijun,ZHOU Xiaolin. Prediction and Countermeasures of Infectious Diseases Based on ARIMA[J]. , 2015, 28(12): 48-.

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