计算机应用与软件2013，Vol.30Issue(4)：217-219,3.DOI:10.3969/j.issn.1000-386x.2013.04.062
广义回归神经网络在乙肝发病数时间序列预测中的应用
APPLICATION OF GENERAL REGRESSION NEURAL NETWORK IN HEPATITIS B INCIDENT CASES TIME SERIES FORECASTING
摘要
Abstract
To explore the practical value of general regression neural networks ( GRNN) in forecasting the incidence number of hepatitis B (HB) , we make use of HB incidence number information from statutory report of mainland of China from 2005 to 2011 and build respectively the GRNN model and the back propagation neural networks (BPNN) model. Results demonstrate that the mean average error (MAE), mean average percentage error (MAPE) and root mean square error (RMSE) of the values fitted and predicted by the GRNN are all lower than those obtained from BPNN. This result indicates that the GRNN has better applied value in forecasting the incidence of HB.关键词
广义回归神经网络/乙肝/时间序列Key words
General regression neural networks/ Hepatitis B/ Time series分类
信息技术与安全科学引用本文复制引用
杨德志..广义回归神经网络在乙肝发病数时间序列预测中的应用[J].计算机应用与软件,2013,30(4):217-219,3.
