Combined classifier–quantifier model: A 2-phases neural model for prediction of wave overtopping at coastal structures

A 2-phases neural prediction method for wave overtopping is developed. The ‘classifier’ predicts whether overtopping occurs or not, i.e. q = 0 or q > 0. If the classifier predicts overtopping q > 0, then the ‘quantifier’ is used to determine the mean overtopping discharge. The overtopping data...

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Bibliographic Details
Published in:Coastal engineering (Amsterdam) 2008-05, Vol.55 (5), p.357-374
Main Authors: Verhaeghe, Hadewych, De Rouck, Julien, van der Meer, Jentsje
Format: Article
Language:English
Subjects:
Artificial neural network
Coastal structures
Earth sciences
Earth, ocean, space
Engineering and environment geology. Geothermics
Engineering geology
Exact sciences and technology
Geomorphology, landform evolution
Marine
Marine and continental quaternary
Neural model
Prediction method
Surficial geology
Wave overtopping
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Summary:A 2-phases neural prediction method for wave overtopping is developed. The ‘classifier’ predicts whether overtopping occurs or not, i.e. q = 0 or q > 0. If the classifier predicts overtopping q > 0, then the ‘quantifier’ is used to determine the mean overtopping discharge. The overtopping database set up within the EC project CLASH (De Rouck, J., Geeraerts, J., 2005. CLASH Final Report, Full Scientific and Technical Report, Ghent University, Belgium) is used to train the networks of the prediction method. The method has an overall predictive capacity, and is able to distinguish negligible from significant overtopping, avoiding large overtopping overpredictions in the area of low overtopping. The prediction method is freely available on http://awww.ugent.be/awww/coastal/verhaeghe2005.html.
ISSN:0378-3839
1872-7379
DOI:10.1016/j.coastaleng.2007.12.002