关键词: 肾综合征出血热, GM(1,1)模型, 广义回归神经网络, 预测

Abstract: Objective To establish an effective model for monitoring and predicting the incidence trend of hemorrhagic fever with renal syndrome(HFRS)in Zhejiang province. Methods HFRS data from 2001 to 2009 in Zhejiang province were used to establish the GM(1,1)-Generalized regression neural network［GM(1,1)-GRNN］model. The GM(1,1)-GRNN model was used to predict the incidence trend of HFRS of the years 2010 to 2011. Results The predicted HFRS incidence with the GM(1,1)-GRNN model for the years 2001 to 2010 closely followed the observe value of the same years, with a relative error of 2.47%, more precise than that of GM(1,1) (11.19%). The forecast values for 2011 was 0.8591 per 10⁵ population. Conclusion The GM(1,1)-GRNN model is highly precise in the prediction of the incidence of HFRS. It provides reliable accurate predicative data, contributing to decision-making regarding the control and prevention of the disease.

Key words: Hemorrhagic fever with renal syndrome, GM(1,1) model, Generalized regression neural network, Prediction