基于BP算法的泥沙含量预测研究

Research on Forecast of Sediment Concentration Based on BP Algorithm

长江口北槽是长江的主航道,泥沙的淤积对航运和河道治理有着极为重要的影响。根据ADCP资料,应用BP算法对长江口的泥沙含量进行了研究,建立了泥沙含量预测模型并根据实测资料进行了验证,实现了根据ADCP资料推求泥沙含量,其结果满足精度要求。

An artificial neural network model is used to estimate the sediment concentration in the Yangtze River Estuary. This is achieved by training the network to extrapolate the sediment concentration from the data collected from ADCP. The selection of water and sediment variables used in the model is based on the prior knowledge of the conventional analyses, based on the dynamic laws of flow and sediment,choosing BP neural network structure for training purpose is addressed by using a constructive back-propagation algorithm, The model parameters are extensively investigated in order to get the most accurate results, and the estimated sediment concentration values agree well with the measured ones.