改进的BP神经网络在流域产沙量预测中的应用  

The Application of Improved BP Network in Amounts of Sediment Forecasting in a Watershed

作　　者：闫志忠[1] 刘金英[1] 

机构地区：[1]吉林大学应用数学研究所,吉林长春130026

出　　处：《世界地质》2002年第3期266-270,共5页World Geology

摘　　要：误差逆传播算法是多层前向网络的典型算法 ,但是其平方误差函数超曲面存在许多局部极小值 ,于是给出了基于输出空间的全局优化BP算法 (globaloptimizationbackpropagationalgorithm ,简称GOB PA)。应用GOBPA ,建立黄河某流域年均产沙量的预测模型。结果表明 。Error back propagation algorithrm is the classical algorithm of multilayer forward net work, but many local minimum value lie on its hypersurface of the square error function, a global optimization algoritlim based on output space is proposed. Using the improved BP neural network,the prediction model of the amounts of a part of Yellow River is constructed .The results showed that the network can forecast the amounts of sediment precisely.

关 键 词：BP神经网络 产沙量 误差逆传播算法 泥沙输移规律 

分 类 号：TV14[水利工程—水力学及河流动力学] TP183[自动化与计算机技术—控制理论与控制工程]