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首页> 外文期刊>International Journal of Water >Daily inflow forecasting for Dukan reservoir in Iraq using artificial neural networks
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Daily inflow forecasting for Dukan reservoir in Iraq using artificial neural networks

机译:基于人工神经网络的伊拉克杜坎水库日流量预测

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摘要

Five ANN model versions were developed for the daily inflow forecasting to Dukan reservoir in Iraq. These models are dependent on the preceding days' lags (1, 2, 3, 4, and 5), respectively. The model versions forecasting correlation coefficients were found to be (94.6%, 94.6%, 95.2%, 95%, and 73%), respectively. The third model was used for forecasting and found capable of forecasting long term daily inflow series of the Dukan reservoir. Moreover it was found also capable of preserving the high and low persistences of this series in addition to the perfect simulation of the recession part and time to peak of the hydrograph.
机译:开发了五个ANN模型版本,用于预测伊拉克杜坎水库的日流量。这些模型分别取决于前几天的滞后时间(1、2、3、4和5)。预测相关系数的模型版本分别为(94.6%,94.6%,95.2%,95%和73%)。使用第三个模型进行预测,发现能够预测杜坎水库的长期日入流量序列。此外,除了对衰退部分和水位曲线达到峰值的时间进行完美模拟外,还发现该系列还可以保留该系列的高低持久性。

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