Journal
OCEAN ENGINEERING
Volume 32, Issue 11-12, Pages 1332-1349Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.oceaneng.2004.11.008
Keywords
breakwater; stability; neural network; reliability based design; Monte Carlo simulation
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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. (c) 2005 Elsevier Ltd. All rights reserved.
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