黄河龙门径流量预测模型研究

河川径流预测是一个十分复杂的问题，生命旋回模型在进行径流趋势预测时具有对资料要求少、计算简单等优点，但由于模型方程的限制，进行预测时得到的序列很难反映径流序列的随机波动变化，且存在预测结果精度不高的缺点。根据黄河龙门水文站提供的49a的径流水文资料。应用神经网络进行预测时和生命旋回模型建模使用，得到预测值。结果表明预测结果明显优于单一的生命旋回模型和神经网络模型，可以用于径流预测。

The River Annual Runoff Prediction Research

The life cycle model is a new long-term prediction model for river runoff,which requires less data,simple calculation.However,due to the physical mechanism,the prediction results of the life cycle model can't reflect the fluctuation and random characteristics of the river annual runoff,and it cannot meet required precision for hydraulics and hydropower engineering management.Aiming at these problems,the life cycle neural network prediction model was put forward.The life cycle neural network model combines l...