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PROCEEDINGS OF THE FOURTH INTERNATIONAL CONFERENCE ON SOFT COMPUTING TECHNOLOGY IN CIVIL, STRUCTURAL AND ENVIRONMENTAL ENGINEERING
Edited by: Y. Tsompanakis, J. Kruis and B.H.V. Topping
Estimation of Regular Wave Run-Up on Slopes of Perforated Coastal Structures Constructed on Sloping Beaches
Department of Civil Engineering, College of Engineering and Islamic Architecture, Umm Al-Qura University, Makkah, Saudi Arabia
M.S. Elbisy, "Estimation of Regular Wave Run-Up on Slopes of Perforated Coastal Structures Constructed on Sloping Beaches", in Y. Tsompanakis, J. Kruis, B.H.V. Topping, (Editors), "Proceedings of the Fourth International Conference on Soft Computing Technology in Civil, Structural and Environmental Engineering", Civil-Comp Press, Stirlingshire, UK, Paper 39, 2015. doi:10.4203/ccp.109.39
Keywords: perforation, surf zone, wave steepness, relative wave height, relative water depth, multiple additive regression trees, neural networks.
The study, described in this paper, was carried out to investigate the regular wave run up phenomenon on the 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, 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 relative wave height 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 percent. The analysis results suggest that the MART-based modeling is effective in predicting wave run-up.
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