RBF神经网络在邯郸市东武仕水库流量预报中的应用

运用RBF神经网络模型对东武仕水库进行了径流预报,以上一时刻的降雨和径流作为神经网络模型的输入,以径流量作为神经网络模型的输出。结果表明,这样的预测方法是非常有效的并且有着更高的精确度。因此,RBF神经网络模型是一个有效的、高精确度的预测径流的方法,可为水资源管理提供可靠的数据支持。

Application of RBF Neural Network model to runoff forecasting for Dongwushi Reservoir in Handan

RBF Neural Network model is applied to the runoff forecasting for Dongwushi Reservoir in Handan. The precipitation and runoff of the previous time duration are taken as the input of the network model and the runoff is taken as the output of the network model. The result shows that this forecasting method is not only quite effective， but also has a higher accuracy. Therefore， RBF Neural Network model is an effective and high precise runoff forecasting method and then can provide reliable data support for water resources management.