Transmission coefficient (Kt) for wave attenuation by vegetation is essential parameter for predicting the wave height. In this paper, based on the experimental data of three kind of artificial vegetation model, genetic programming (GP), artificial neural networks (ANNs) and multivariate non-linear regression (MNLR) were used to analyze the dimensionless factors including Ursell number (Ur), relative width (RB) relative height (α) and volume fraction (φ). The proposed GP formulae were compared with MNLR and ANNs. The predictions of GP models were in good agreement with measured data, and outperformed MNLR equations. Otherwise, GP and ANNs were used to obtain the weight of each factor. The results can provide a reference for the artificial planting of the three plants.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.