Artificial intelligence applied to plane wave reflection at submerged breakwaters

• Tipo: Artigo em Revista Científica Internacional
• Data: 2011

Autores

Castro, A (Autor) Outra; Francisco Taveira Pinto (Autor) FEUP; Iglesias, G (Autor) Outra

Revista

Título: JOURNAL OF HYDRAULIC RESEARCH

Vol. 49

Páginas: 465-472

ISSN: 0022-1686

Indexação

ISI Web of Knowledge - 5 Citações

ISI Web of Science

Scopus - 11 Citações

Classificação Científica

FOS: Ciências da engenharia e tecnologias > Outras ciências da engenharia e tecnologias

CORDIS: Ciências Tecnológicas > Engenharia

Outras Informações

ID Authenticus: P-002-XBF

DOI: 10.1080/00221686.2011.568197

Abstract (EN): 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.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 8