Solitary wave attenuation characteristics of mangroves and multi-parameter prediction model

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@Article{YIN:2023:oceaneng,

• author = "Zegao Yin and Jiahao Li and Yanxu Wang and Haojian Wang and Tianxu Yin",
• title = "Solitary wave attenuation characteristics of mangroves and multi-parameter prediction model",
• journal = "Ocean Engineering",
• volume = "285",
• pages = "115372",
• year = "2023",
• ISSN = "0029-8018",
• DOI = "doi:10.1016/j.oceaneng.2023.115372",
• URL = "https://www.sciencedirect.com/science/article/pii/S0029801823017560",
• keywords = "genetic algorithms, genetic programming, Solitary waves, Mangrove forest, Rigid cylindrical vegetation, Wave attenuation coefficient, Back propagation neural network",
• abstract = "Mangroves contribute to wave attenuation and improve coastal disaster prevention. Extensive studies have been conducted to explore wave attenuation by mangroves using rigid cylinders. However, few studies have investigated interactions between solitary waves and mangroves with roots. Therefore, laboratory experiments are conducted to investigate wave dissipation along a 1:10 scale Rhizophora mangrove forest under solitary waves, and wave attenuation characteristics are analyzed to highlight the significance of the effects of mangrove roots on wave damping. A numerical model of mangrove with roots is conducted by combining cylinder and porous media, where the trunk is considered as a cylinder and roots are simulated by introducing the resistance source term and porosity effect into the momentum equation. Results show that wave parameters (still water depth and incident wave height) and a vegetation parameter (vegetation submerged projected area) are the dominant variables affecting wave attenuation. In addition, multivariate nonlinear regression, genetic programming, and back propagation (BP) neural network are employed to explore the relationship between the wave attenuation coefficient and other related dimensionless parameters. Results show that the BP model is more accurate in predicting the wave attenuation coefficient as compared with other methods and thus can predict solitary wave attenuation in mangrove forests",

}

Genetic Programming entries for Zegao Yin Jiahao Li Yanxu Wang Haojian Wang Tianxu Yin

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