【摘要】 针对经典BP神经网络模型,增设误差修正系数,实现网络误差修正权重倾向于输出样本的较大值,据此提出了一种计算输入输出向量的归一化公式,并建立了具有洪峰识别的洪水预报BP网络预报模型。采用新模型对宜昌水文站典型年实测流量过程进行了预测检验,其结果与实测值较吻合,对流量过程及洪峰流量过程的预报精度较经典BP模型高。更多还原

【Abstract】 In this paper,the BP neural network model for flood forecasting is improved by adding the correct coefficient,and error weights for bigger output examplevalues are introduced into BP model to meet the peak flood.This model can simulate and forecast different characters of discharge process and its peak flood.The standardized formulas are proposed for calculating the vector of input and output.Finally,two years result of measured and forecasting discharge process at Yichang Station have been obtained,it can be found that forecast result agrees well with the measured data.更多还原