Journal
OCEAN ENGINEERING
Volume 31, Issue 17-18, Pages 2073-2086Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.oceaneng.2004.05.006
Keywords
liquefaction; wave loading; poro-elastic model; artificial neural network
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The prediction of wave-induced liquefaction has been recognised by coastal geotechnical engineers as an important factor when considering the design of marine structures. All existing models have been based on conventional approaches of engineering mechanics with limited laboratory work. In this study, we propose an alternative approach for the prediction of the maximum liquefaction depth, based on neural network (NN). Unlike previous engineering mechanics approaches, the proposed NN model is based on data learning knowledge, rather than on knowledge of mechanisms. Numerical examples demonstrate the capacity of the proposed NN model for the prediction of wave-induced liquefaction depth, which provides civil engineers with another effective tool. (C) 2004 Elsevier Ltd. All rights reserved.
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