军事医学2017，Vol.41Issue(4)：287-290,4.DOI:10.7644/j.issn.1674-9960.2017.04.009
季节分解法和ARIMA法预测乌鲁木齐市肺结核发病趋势效果分析
Seasonal decomposition and ARIMA methods in prediction of tuberculosis incidence in Urumqi,China
摘要
Abstract
Objective To compare the accuracy of the seasonal time series decomposition method and autoregressive integrated moving average (ARIMA) in the prediction of incidence of tuberculosis(TB) in order to facilitate early-warning.Methods The seasonal decomposition model and ARIMA model were constructed by SPSS20.0 software based on time series of monthly TB incidence between January 2005 and December 2014 in Urumqi,China.The obtained models were used to forecast the monthly incidence in 2015 and compared with the actual incidence respectively.Results Between 2005 and 2014,the incidence of TB was higher during March,April and May in Urumqi.A linear fitting model and a cubic curve fitting model were constructed by the time series seasonal decomposition method.The mean absolute percentage error (MAPE) of each predicted monthly incidence in 2015 was 18.75% and 92.25%,respectively.The predicted values of the linear model were lower than actual values and the predicted values of the cubic curve model were higher than actual values.An ARIMA (2,1,1) (1,1,0)12 fitting model was established by ARIMA method.The MAPE of each predicted monthly incidence in 2015 was 9.46% and there were no significant differences between the predicted and actual values.Conclusion The ARIMA method is better than the seasonal decomposition method for predicting the monthly incidence of TB in Urumqi.关键词
时间序列分析/季节分解/ARIMA模型/肺结核/预测Key words
time series analysis/seasonal decomposition/autoregressive integrated moving average model/tuberculosis/prediction分类
医药卫生引用本文复制引用
温亮,张秀山,李承毅,褚宸一,王勇,陈阳贵,李申龙..季节分解法和ARIMA法预测乌鲁木齐市肺结核发病趋势效果分析[J].军事医学,2017,41(4):287-290,4.基金项目
全军后勤科研重大项目(AWS14R013) （AWS14R013）
全军后勤科研重点项目(BWS14C051) （BWS14C051）
新疆维吾尔自治区自然科学基金资助项目(201442137-20) （201442137-20）
