传染病预测的建模与计算机仿真研究

Modeling and Simulation Research on Infectious Disease Forecasting

研究传染病准确预测问题,传染病变化具有突发性、季节性和周期性等特点,传染病与环境污染,人群之间交流有关,随机性强。传统预测方法无法全面描述突发性、季节性及周期性变化规律,传染病预测结果的精度低。为了传染病准确预测,根据传染病变化特点,提出一种ARIMA的传染病预测模型。模型首先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,然后利用ARIMA对将平稳后的数据进行建模,采用某市乙型肝炎发病率数据进行仿真,实验结果表明,ARIMA模型能够很好捕捉传染病变化规律,提高了预测精度,是一种有效的传染病预测方法。

Research forecasting problem of infection diseases.The infectious diseases have the features of sudden changes,seasonal and periodical,and the traditional forecasting methods cannot fully describe the change rule,so that the accuracy of infectious is lower.In order to improve the accuracy of predicted results of infectious diseases,according to the changing characteristics of infectious diseases,the paper proposed a infectious disease forecast model based on ARIMA.Firstly,the original data model was smoothed to eliminate the suddenness,seasonal and periodicity,then ARIMA model was used for forecasting.An incidence of city hepatitis B was used to test the model,and the experimental results show that the ARIMA model can capture infectious diseases change rule very well and improve the forecasting accuracy.Tt is a good infectious disease forecasting method.