Application of ARIMA Model based on Empirical Mode Decomposition in Pulmonary Tuberculosis Prediction in Shanxi Province
10.11783/j.issn.1002－3674.2025.02.004
- VernacularTitle:基于经验模态分解的ARIMA模型在山西省肺结核预测中的应用
- Author:
Jing LIU
1
;
Ruiqing ZHAO
;
Zhiyang ZHAO
Author Information
1. 山西医科大学公共卫生学院卫生统计学教研室(030001)
- Publication Type:Journal Article
- Keywords:
Pulmonary Tuberculosis;
EMD;
ARIMA;
Forecast
- From:
Chinese Journal of Health Statistics
2025;42(2):175-179
- CountryChina
- Language:Chinese
-
Abstract:
Objective To explore the prediction performance of the autoregressive summation moving average(ARIMA)model based on empirical mode decomposition(EMD)for the prevalence trend of tuberculosis,to provide method support for the prediction of tuberculosis,and to provide ideas for the prediction of other infectious diseases.Methods The monthly data of pulmonary tuberculosis incidence in Shanxi Province from January 2008 to December 2018 were collected and sorted.The last three months,six months,nine months and one year of the data were used as the test set to evaluate the model prediction effect,and the training set was the remaining data of the corresponding sequence.The EMD-ARIMA model was constructed to predict and compared with the single ARIMA model.Results The predicted errors of EMD-ARIMA model for the next three months,six months,nine months and one year were all smaller than the errors of ARIMA model.Conclusion Compared with single ARIMA model,EMD-ARIMA model can improve the prediction accuracy and predict the incidence of pulmonary tuberculosis,and provide effective theoretical reference for disease control and prevention.
