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Prediction of Seepage Quantities of Earthfill Dam Foundation Based on Artificial Neural Network

机译:基于人工神经网络的土石坝坝基渗流量预测。

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In artificial neural network(ANN)method, the information treatment of the network are finished through interaction of neurones of the network.There are a series of advantages in the methodology,such as high degree non-linear,self-adaptatinn,self-learning,etc.Therefore the ANN method is used widely in the fields of prediction of physical quantities.ln most cases, seepage equations show strong non-linear characteristics. This paper presents and establishes an ANN model based on the training method of learning into groups.Combining the practice of Xixia Researvoir, application of the ANN model to prediction of seepage quantities of the dam foundation is studied. There are high degree accuracy in the prediction result through using the ANN method.The results demonstrate that this method is widely available for the fields of dam safety monitoring and operation.
机译:在人工神经网络(ANN)方法中,网络的信息处理是通过网络神经元的交互作用完成的。该方法具有一系列优点,例如高度非线性,自适应,自学习因此,人工神经网络方法被广泛用于物理量的预测领域。在大多数情况下,渗流方程表现出很强的非线性特性。本文基于分组学习的训练方法,提出并建立了一个人工神经网络模型。结合西夏研究的实践,研究了人工神经网络模型在大坝基础渗流量预测中的应用。人工神经网络方法对预测结果具有较高的准确度。结果表明,该方法可广泛应用于大坝安全监测和运行领域。

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