水库流域年均径流模型的灰色神经网络分析

水库流域年均径流量受诸多因素影响，而年均径流量对水库流域水资源经济开发利用作用显著。利用改进后的灰色模型对某水库流域实测数据的年均径流模型进行了相关影响因子的建模分析，将预测值与实测值作为神经网络的训练样本，对网络进行训练并分别进行识别，同时进行误差分析对比。结果表明，灰色神经网络能对水库流域年均径流模型进行预测分析，精度较高，所得结果与实际观测数据基本相符。

Grey neural network analysis on annual average runoff model of reservoir

The annual average runoff of reservoir is affected by a great deal of factors but it has great importance for the water resources exploitation and utilization of a reservoir valley. The improved grey model is used to analyze the relative affecting factors of the annual average runoff model based on the measured data from a reservoir valley and the prediction and measured data are used as the samples of neural network to train the network and identify them individually, then error analysis and comparison are made. The results showed that the grey neural network can be used to predict and analyze the annual average runoff model of reservoir valley in a high precision, and its results are basically comply with the measured data.