基于BP神经网络的长江口北支河槽容积分析

Analysis of the channel cubage of the North Branch of the Yangtze River Estuary with BP neural network

根据实测水文及泥沙等资料,采用现在较成熟的且应用广泛的BP人工神经网络建立了北支0 m以下河槽容积与大通流量、大通输沙量及北支分流比3个因子间的神经网络模型,网络结构为3-1-7-1,通过选择合适的参数,模型训练较好,预测结果与线性回归模型预测结果相近,说明BP神经网络模型能够广泛应用于河口水文等方面的预报。

Based on the hydrology and sediment data,an artificial neural network model was established to study the relationship among the channel cubage under the 0 m-isobath in North Branch,the flow and sediment discharge at Datong gauging station and the flow split ratio of the North Branch.The structure of the network model was fixed on 3-1-7-1.The network model was trained and tested by choosing appropriate parameters.The computation results of BP artificial neural network agree well with that of multiple linear regressions.It can be concluded that BP arti-ficial neural network may be used to predict the hydrological factors such as sediment discharge in estuary.