Prediction of local scour around circular piles under waves using a novel artificial intelligence approach期刊界 All Journals 搜尽天下杂志传播学术成果专业期刊搜索期刊信息化学术搜索

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Prediction of local scour around circular piles under waves using a novel artificial intelligence approach

Authors:	Iman Ahmadianfar Xuefeng Chu

Institution:	1. Department of Civil Engineering, Behbahan Khatam Alanbia University of Technology, Behbahan, Iran;2. https://orcid.org/0000-0002-9960-1222;3. Department of Civil &4. Environmental Engineering, North Dakota State University, Fargo, ND, USAhttps://orcid.org/0000-0003-0322-0271

Abstract:	Abstract The scour phenomena around vertical piles in oceans and under waves may influence the structure stability. Therefore, accurately predicting the scour depth is an important task in the design of piles. Empirical approaches often do not provide the required accuracy compared with data mining methods for modeling such complex processes. The main objective of this study is to develop three data-driven methods, locally weighted linear regression (LWLR), support vector machine (SVR), and multivariate linear regression (MLR) to predict the scour depth around vertical piles due to waves in a sand bed. It is the first effort to develop the LWLR to predict scour depth around vertical piles. The models simulate the scour depth mainly based on Shields parameter, pile Reynolds number, grain Reynolds number, Keulegan–Carpenter number, and sediment number. 111 laboratory datasets, derived from several experimental studies, were used for the modeling. The results indicated that the LWLR provided highly accurate predictions of the scour depths around piles (R?=?0.939 and RMSE = 0.075). Overall, this study demonstrated that the LWLR can be used as a valuable tool to predict the wave-induced scour around piles.

Keywords:	Wave scour locally weighted linear regression (LWLR) supported vector regression (SVR) multi linear regression (MLR) circular piles

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