水资源与水工程学报2011，Vol.22Issue(1)：94-97,4.
RBF神经网络模型在金沟河流域径流预测中的应用
Application of RBF neural network model to the prediction of runoff in Jingouhe River Basin
摘要
Abstract
The traditional prediction methods are hard to describe the evolution rule of runoff which is a complicated non-linear time sequence system.Based on 1957 -2003 annual runoff observed data in Bajiahu hydrological station in the Jingouhe River Basin, a runoff prediction model with RBF neural network was established in Matlab environment after the subtraction of the data was studied using normalization and autocorrelation algorithms.The results indicated that the prediction model with RBF neural network had higher forecasting accuracy and shorter time consumption comparing with the traditional BP neural network.It is an effective method for runoff prediction.关键词
径向基神经网络/归一化/MATLAB/径流预测分类
天文与地球科学引用本文复制引用
任磊,岳春芳,何训江..RBF神经网络模型在金沟河流域径流预测中的应用[J].水资源与水工程学报,2011,22(1):94-97,4.基金项目
教育部科学技术研究重点项目(209140) （209140）
新疆农业大学校前期资助课题 （）
新疆水利水电工程重点学科资助 （）
