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dc.contributor.authorJeng, Dong-Shengen_US
dc.contributor.authorBlumenstein, Michaelen_US
dc.contributor.editorMichael E. McCormick, Rameswar Bhattacharyyaen_US
dc.date.accessioned2017-04-24T10:08:42Z
dc.date.available2017-04-24T10:08:42Z
dc.date.issued2004en_US
dc.identifier.issn00298018en_US
dc.identifier.doi10.1016/j.oceaneng.2004.05.006en_US
dc.identifier.urihttp://hdl.handle.net/10072/5141
dc.description.abstractThe 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.en_US
dc.description.peerreviewedYesen_US
dc.description.publicationstatusYesen_US
dc.languageEnglishen_US
dc.language.isoen_US
dc.publisherPergamon-Elsevier Science Ltd.en_US
dc.publisher.placeUKen_US
dc.relation.ispartofpagefrom2073en_US
dc.relation.ispartofpageto2086en_US
dc.relation.ispartofissue17-18en_US
dc.relation.ispartofjournalOcean Engineeringen_US
dc.relation.ispartofvolume31en_US
dc.subject.fieldofresearchcode291205en_US
dc.subject.fieldofresearchcode280212en_US
dc.titleNeural network model for the prediction of wave-induced liquefaction potentialen_US
dc.typeJournal articleen_US
dc.type.descriptionC1 - Peer Reviewed (HERDC)en_US
dc.type.codeC - Journal Articlesen_US
gro.facultyGriffith Sciences, Griffith School of Engineeringen_US
gro.date.issued2015-06-03T02:44:30Z
gro.hasfulltextNo Full Text


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