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Estimation of Hydraulic Characteristics around Artificial Reef using Neural Network: A Case Study of Wave Trapping Artificial Reef

机译:用神经网络估算人工鱼礁周围水力特征 - 以捕波人工鱼礁为例

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摘要

This study aims to develop a highly accurate method for an estimation of hydraulic characteristics around an artificial reef by using an artificial neural network, instead of a conventional method using a regression analysis. The wave trapping artificial reef is chosen as the structure of an artificial reef, and transmission coefficient and wave setup behind the reef are focused as hydraulic characteristics. For the training of the artificial neural network, the Levenberg-Marquardt method with Bayesian regulation is employed. Predictions of transmission coefficient and wave setup from the trained network agreed well with the experimental results comparing with predicted ones from the method using a regression analysis.
机译:这项研究的目的是开发一种高精度的方法,代替使用回归分析的传统方法,通过使用人工神经网络估算人工鱼礁周围的水力特性。选择捕波人工礁作为人工礁的结构,并重点研究礁石后面的传播系数和波浪形成作为水力特性。对于人工神经网络的训练,采用具有贝叶斯调节的Levenberg-Marquardt方法。与通过回归分析从该方法得到的预测结果相比,来自训练网络的传输系数和波建立的预测与实验结果非常吻合。

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