Solitary wave attenuation characteristics of mangroves and multi-parameter prediction model
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- @Article{YIN:2023:oceaneng,
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author = "Zegao Yin and Jiahao Li and Yanxu Wang and
Haojian Wang and Tianxu Yin",
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title = "Solitary wave attenuation characteristics of mangroves
and multi-parameter prediction model",
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journal = "Ocean Engineering",
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volume = "285",
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pages = "115372",
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year = "2023",
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ISSN = "0029-8018",
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DOI = "doi:10.1016/j.oceaneng.2023.115372",
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URL = "https://www.sciencedirect.com/science/article/pii/S0029801823017560",
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keywords = "genetic algorithms, genetic programming, Solitary
waves, Mangrove forest, Rigid cylindrical vegetation,
Wave attenuation coefficient, Back propagation neural
network",
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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
Citations