Neural network for design and reliability analysis of rubble mound breakwaters

Artificial neural networks were applied to the design of rubble mound breakwater. Five neural networks with different network structures were trained with the same training data. Then they were compared with conventional empirical model and one another. It was found that the neural network technique...

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Bibliographic Details
Published in:Ocean engineering 2005-08, Vol.32 (11), p.1332-1349
Main Authors: Kim, Dong Hyawn, Park, Woo Sun
Format: Article
Language:English
Subjects:
Applied sciences
Breakwater
Buildings. Public works
Computation methods. Tables. Charts
Exact sciences and technology
Hydraulic constructions
Marine
Monte Carlo simulation
Neural network
Port facilities and coastal structures. Lighthouses and beacons
Reliability based design
Stability
Structural analysis. Stresses
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Summary:Artificial neural networks were applied to the design of rubble mound breakwater. Five neural networks with different network structures were trained with the same training data. Then they were compared with conventional empirical model and one another. It was found that the neural network technique gives more accurate results than conventional empirical model and the extent of accuracy can be affected by the structure of neural network. After that, how to integrate the trained neural network into reliability analysis technique is proposed. Since the neural network technique shows better performance than empirical model based approach in breakwater design, it is expected that the neural network integrated reliability analysis gives more improved results for probability of failure than it is done with empirical model.
ISSN:0029-8018
1873-5258
DOI:10.1016/j.oceaneng.2004.11.008