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Artificial intelligence applied to plane wave reflection at submerged breakwaters / Alberte Castro in Journal of hydraulic research, Vol. 49 N° 4 (Juillet/Août 2011) 

Public ISBD [article]  in Journal of hydraulic research > Vol. 49 N° 4 (Juillet/Août 2011) . - pp. 465-472 Titre : Artificial intelligence applied to plane wave reflection at submerged breakwaters Type de document : texte imprimé Auteurs : Alberte Castro, Auteur ; Francisco Taveira Pinto, Auteur ; Gregorio Iglesias, Auteur Année de publication : 2011 Article en page(s) : pp. 465-472 Note générale : Hydraulique Langues : Anglais (eng) Mots-clés : Artificial  intelligence  Artificial  neural  network  Shoreline  erosion  Submerged  breakwater  Wave  reflection Index. décimale : 627 Ingénierie des cours d'eau naturels, des ports, des rades et des cotes. Installations de navigation, de dragage, de récupération et de sauvetage. Barrages et centrales électriques hydrauliques Résumé : The reflection process at submerged breakwaters is investigated by means of an artificial neural network (ANN) model. This model estimates the reflection coefficient based on three dimensionless products which are functions of the wave parameters and the characteristics of the submerged breakwater. The data used for training the model were obtained from an extensive experimental campaign in which seven models of submerged breakwaters were tested under irregular waves combinations. To choose the neural network architecture best suited for this problem, the performances of 400 ANN models involving 10 different architectures are assessed. Having selected the most appropiate architecture, the model was succesfully trained and validated. Excellent agreement was achieved between the model's results and the experimental data. The new artificial intelligence model can be used as a virtual laboratory to predict the reflection coefficient without a need for a physical model test. DEWEY : 627 ISSN : 0022-1686 En ligne : http://www.tandfonline.com/doi/abs/10.1080/00221686.2011.568197 [article] Artificial intelligence applied to plane wave reflection at submerged breakwaters [texte imprimé] / Alberte Castro, Auteur ; Francisco Taveira Pinto, Auteur ; Gregorio Iglesias, Auteur . - 2011 . - pp. 465-472. Hydraulique Langues : Anglais (eng) in Journal of hydraulic research > Vol. 49 N° 4 (Juillet/Août 2011) . - pp. 465-472 Mots-clés : Artificial  intelligence  Artificial  neural  network  Shoreline  erosion  Submerged  breakwater  Wave  reflection Index. décimale : 627 Ingénierie des cours d'eau naturels, des ports, des rades et des cotes. Installations de navigation, de dragage, de récupération et de sauvetage. Barrages et centrales électriques hydrauliques Résumé : The reflection process at submerged breakwaters is investigated by means of an artificial neural network (ANN) model. This model estimates the reflection coefficient based on three dimensionless products which are functions of the wave parameters and the characteristics of the submerged breakwater. The data used for training the model were obtained from an extensive experimental campaign in which seven models of submerged breakwaters were tested under irregular waves combinations. To choose the neural network architecture best suited for this problem, the performances of 400 ANN models involving 10 different architectures are assessed. Having selected the most appropiate architecture, the model was succesfully trained and validated. Excellent agreement was achieved between the model's results and the experimental data. The new artificial intelligence model can be used as a virtual laboratory to predict the reflection coefficient without a need for a physical model test. DEWEY : 627 ISSN : 0022-1686 En ligne : http://www.tandfonline.com/doi/abs/10.1080/00221686.2011.568197