Abstract
The European Union funded project DELOS was focused on wave transmission and an extensive database on low-crested rubble mound structures was generated. During DELOS, new empirical wave transmission formulae were derived. These formulae still showed a considerable scatter due to a limited number of parameters included. Neural networks based on a homogeneous database have resulted in a useful prediction model for wave overtopping within the EU project CLASH. The successful methodology of CLASH is applied within this study. The aim of this study is to improve the prediction of wave transmission in comparison to the empirical DELOS formulae with help of a prediction model based on neural networks. This paper gives a overview of the contents of the composed homogeneous database and gives insight in the capacity and accuracy of the final prediction model. The final prediction model includes 9 input parameters, which is more than at present in the existing hand-derived empirical formulae. The prediction model is accurate in predicting wave transmission for both smooth and mound low-crested structures.
Original language | English |
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Title of host publication | Proceedings of the 30th international conference coastal engineering 2006 |
Editors | J McKee Smith |
Place of Publication | Singapore |
Publisher | World Scientific |
Pages | 4932-4944 |
Number of pages | 13 |
ISBN (Print) | 9789812706362 |
DOIs | |
Publication status | Published - 2007 |
Event | 30th International Conference on Coastal Engineering, ICCE 2006 - San Diego, United States Duration: 3 Sept 2006 → 8 Sept 2006 |
Publication series
Name | |
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Publisher | World Scientific |
Name | |
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Volume | 5 |
Conference
Conference | 30th International Conference on Coastal Engineering, ICCE 2006 |
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Abbreviated title | ICCE 2006 |
Country/Territory | United States |
City | San Diego |
Period | 3/09/06 → 8/09/06 |