Based on the artificial neural network (ANN), a real-time flood forecasting model is proposed.
建立了一种基于神经网络的洪水实时预报模型。
Finally, it is concluded that the best model selection in the light of different predicted information will improve precision for flood forecasting.
由此还得出另一个结论：在实时洪水预报中，根据不同的预知信息实时选择最佳的模型，能提高洪水预报的精度。
The proposed flood model is applicable to design and forecasting for medium and small basins, especially in data-lacking regions.
该模型适用于中、小流域的设计与预报，尤其适用于无资料地区。
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