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Titulo: A Virtual Laboratory for stability test of rubble-mound breakwaters
Tipo: revista nacional
Fecha: 2008
Revista: Ocean Engineering
JCR Journal; Impact Factor: 0.857
Citas Scopus: 5 Citas Google Scholar: 1
Volumen: 35
Paginas: 1113-1120
ISSN: 0029-8018
Editorial: Elsevier
Paises Bajos


The prediction of rubble-mound breakwater damage under wave action has usually relied on costly and time-consuming physical model tests. In this work, artificial neural networks (ANNs) are applied to estimate the outcome of a physical model throughout an experimental campaign comprising of 127 stability tests. In order to choose the network best suited to the problem data, five different activation function options and 38 network architectures are compared. The good agreement found between the physical model and the neural network shows that an ANN may well serve as a virtual laboratory, reducing the number of physical model tests necessary for a project.

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