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Mid- and long term hydrologic forecasting for drainage area based on WNN and FRM

机译:基于WNN和FRM的流域中长期水文预报。

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摘要

Mid- and long term hydrologic forecasting of drainage area is a difficult issue in engineering design and hydrological process simulation. Combined with wavelet neural network (WNN) to calculate and forecast the weight of model, fuzzy recognition model (FRM) is used to fit and predict mid- and long term hydrological phenomena, and the regression equation with correlation coefficient that more than 0.90 is adopted as fit equation to evaluate and verify this process. The result shows that this method is reasonable and simple, and it can be applied for forecasting work
机译:流域中长期水文预报是工程设计和水文过程模拟中的难题。结合小波神经网络(WNN)计算和预测模型权重,采用模糊识别模型(FRM)拟合和预测中长期水文现象,采用相关系数大于0.90的回归方程。作为拟合方程来评估和验证该过程。结果表明,该方法合理,简单,可用于预测工作。

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