Prediction of schistosomiasis infection rates of population based on ARIMA-NARNN model
10.16250/j.32.1374.2016089
- VernacularTitle:基于ARIMA-NARNN组合模型的血吸虫感染率预测研究
- Author:
Kewei WANG
;
Yu WU
;
Jinping LI
;
Yuyu JIANG
- Keywords:
Autoregressive integrated moving average model (ARIMA);
Nonlinear auto-regressive neural network (NARNN);
Time series;
Schistosomiasis;
Prediction
- From:
Chinese Journal of Schistosomiasis Control
2016;28(6):630-634
- CountryChina
- Language:Chinese
-
Abstract:
Objective To explore the effect of the autoregressive integrated moving average model?nonlinear auto?regressive neural network(ARIMA?NARNN)model on predicting schistosomiasis infection rates of population. Methods The ARIMA model,NARNN model and ARIMA?NARNN model were established based on monthly schistosomiasis infection rates from Janu?ary 2005 to February 2015 in Jiangsu Province,China. The fitting and prediction performances of the three models were com?pared. Results Compared to the ARIMA model and NARNN model,the mean square error(MSE),mean absolute error (MAE)and mean absolute percentage error(MAPE)of the ARIMA?NARNN model were the least with the values of 0.011 1, 0.090 0 and 0.282 4,respectively. Conclusion The ARIMA?NARNN model could effectively fit and predict schistosomiasis in?fection rates of population,which might have a great application value for the prevention and control of schistosomiasis.
