论文探索了人工神经网络方法(ANN)在河道洪水预报中的应用；该结果具有一定实用前景。
The artificial neural network (Ann) method is studied for use in river channel flood forecasting, the result show that the method can be applied in practice.
提出和讨论了基于马斯京根流量演算河道洪水实时预报的半自适应滤波模型。
Based on the Kilman filter theory and Muskingum method, the half self adaptive updating Kilman filter model of channel flow routing has been developed for real time application of flood forecasts.
该模型的特点是对河道地形要求不高，能够满足水沙输移实时预报的要求。
The model can be used for real time prediction of flow and sediment transport in multiple connected river channels and is suitable for the area where topography map is not sufficient.
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