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Analytical and artificial neural network models to estimate the discharge coefficient for ogee spillway

机译:分析和人工神经网络模型来估算ogee溢洪道的排放系数

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In this study, analytical and Artificial Neural Network (ANN) model were used for determine the discharge coefficient of Ogee Spillways. For this aim, discharge coefficients of 11 different heads were calculated by using a test flume having 7.5 cm width, 15 cm depth and 5 m length, in the laboratory. Discharge coefficients were also computed by the formula for the same heads measured in the laboratory to investigate the accuracy of experimental setup. An ANN model was set by using the experimental results in order to estimate the discharge coefficient. Then, the performance of the ANN model was investigated. As the result, the coefficient of determination between ANN model and experimental setup is found R2= 0.98. ANN model is show a good consistency with experimental results.
机译:在该研究中,分析和人工神经网络(ANN)模型用于确定ogee溢洪道的放电系数。为此目的,通过使用具有7.5cm宽度,15cm深度和5米长的测试水槽来计算11个不同头部的放电系数,在实验室中计算。通过在实验室中测量的相同头部的公式计算放电系数,以研究实验设置的准确性。通过使用实验结果来设定ANN模型,以估计放电系数。然后,研究了ANN模型的性能。结果,找到了ANN模型与实验设置之间的测定系数R2 = 0.98。 ANN模型显示出与实验结果的良好一致性。

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