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Estimation of regular wave run-up on slopes of perforated coastal structures constructed on sloping beaches

机译:在倾斜海滩上建造的带孔沿海结构的边坡上的规则波传播估计

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This study was carried out to investigate the regular wave run-up phenomenon on smooth slopes of perforated coastal structures constructed on sloping beaches and the various parameters that affect wave run-up. Experiments were conducted using various hydraulic and structural parameters. The relative coastal structure distance, relative depth, relative wave height, beach slope, coastal structure inclination, and surf similarity parameter were found to be positively correlated to the relative wave run-up. The wave steepness and coastal structure perforation percentage were found to be negatively correlated to the relative wave run-up. The results also show that the coastal structure perforation percentage plays a dominant role in the attenuation of short waves but a less significant role in the attenuation of long waves. The quantitative analyses were performed using multiple additive regression trees (MART) and multilayer perceptron neural networks (MLP) methods. The results indicate that the MART method's prediction accuracy and avoidance of over-fitting were superior to those of the MLP method. The percentage improvement in the root mean square error of the MART model over the MLP model in predicting relative wave run-up was 57.56%. The analysis results suggest that MART-based modeling is effective in predicting wave run-up. (C) 2015 Elsevier Ltd. All rights reserved.
机译:这项研究旨在调查在倾斜海滩上建造的多孔沿海结构的光滑斜坡上的规则波浪上升现象以及影响波浪上升的各种参数。使用各种水力和结构参数进行了实验。相对海岸结构距离,相对深度,相对波高,海滩坡度,海岸结构倾斜度和海浪相似性参数与相对波径呈正相关。发现波的陡度和沿海结构的射孔百分比与相对波上升呈负相关。结果还表明,沿海结构的穿孔率在短波的衰减中起主要作用,而在长波的衰减中作用较小。使用多个加性回归树(MART)和多层感知器神经网络(MLP)方法进行了定量分析。结果表明,MART方法的预测准确性和避免过度拟合的能力优于MLP方法。在预测相对波上升方面,MART模型的均方根误差相对于MLP模型的改进百分比为57.56%。分析结果表明,基于MART的建模有效地预测了波的上升。 (C)2015 Elsevier Ltd.保留所有权利。

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