七里街水文站实时洪水预报神经网络模型

A Study on Model for Actual Flood Forecast in Qili Street Hydrometric Station

采用人工神经网络方法，建立福建省闽江建溪流域七里街水文站实时洪水过程预报的３ 层前馈反向传播神经网络模型， 经检验预测精度为８３．３０％ ， 符合该区洪水预报规范， 准确率比较高． 其结果表明，

This article introduced the method of artificial neural network,and build a model of three level feed toward back propagation neural network to simulate actual flood forecast in Qili street hydrometric station of the Minjiang river valley.The simulating precision of BP model was 83 3%,which reacheed the predictable standard of flood in this area.This study showed that the artificial neural network model could be used to simulate actual flood dynamically.