2011-2021年浙江省肺结核发病率预测:基于三体模型和三体预测法OA北大核心CSTPCD
Prediction of pulmonary tuberculosis incidence in Zhejiang Province from 2011 to 2021:based on trinity model and trinity forecasting method
目的 研究三体模型和三体预测法在预测肺结核发病趋势中的应用.方法 使用浙江省2011-2021年肺结核月度发病率数据,基于三体模型和三体预测法构建预测模型,并评估该预测模型的预测性能.结果 基于三体模型和三体预测法获得的预测模型1和预测模型2的平均相对预测误差分别为7.94％、8.43％,而使用自回归移动平均(ARIMA)模型获得的平均相对预测误差为8.87％,以上平均相对预测误差均处于区间(7.9％～8.9％),显示预测模型表现优秀.结论 三体模型是表现优秀的时间序列预测模型,三体预测法是表现优秀的时间序列预测方法,具有较高的应用价值.
Objective To study the application of the trinity model and trinity forecasting method in predicting the incidence trend of pulmonary tuberculosis(PTB).Methods By applying the monthly PTB incidence data in Zhe-jiang Province from 2011 to 2021,a prediction model was constructed based on the trinity model and trinity forecas-ting method.Predictive performance of the model was evaluated.Results The mean relative prediction errors of model 1 and model 2 based on trinity model and trinity forecasting method were 7.94％and 8.43％,respectively.The mean relative prediction error obtained by adopting autoregressive integrated moving average(ARIMA)model was 8.87％,and the above mean relative prediction error were all in the range of 7.9％-8.9％,which presented an excellent performance of the forecasting model.Conclusion The trinity model is an excellent time series forecasting model,and the trinity forecasting method is an excellent time series forecasting method,with high application value.
楼润平;潘依菲;王棣楠;张允馨
海南大学国际商学院,海南海口 570228
预防医学
肺结核发病率三体模型三体预测法时间序列预测误差
incidence of pulmonary tuberculosistrinity modeltrinity forecasting methodtime seriespredic-ting error
《中国感染控制杂志》 2024 (007)
806-811 / 6
海南省自然科学基金高层次人才项目(723RC462)
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