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dc.contributor.authorCha, Daeho Fred
dc.contributor.authorZhang, Hong
dc.contributor.authorBlumenstein, Michael
dc.date.accessioned2018-11-14T12:30:33Z
dc.date.available2018-11-14T12:30:33Z
dc.date.issued2011
dc.date.modified2013-05-29T08:46:03Z
dc.identifier.issn0029-8018
dc.identifier.doi10.1016/j.oceaneng.2010.08.002
dc.identifier.urihttp://hdl.handle.net/10072/37529
dc.description.abstractIn the last few decades, considerable efforts have been devoted to the phenomenon of wave-induced liquefactions, because it is one of the most important factors for analysing the seabed and designing marine structures. Although numerous studies of wave-induced liquefaction have been carried out, comparatively little is known about the impact of liquefaction on marine structures. Furthermore, most previous researches have focused on complicated mathematical theories and some laboratory work. In the present study, a data dependent approach for the prediction of the wave-induced liquefaction depth in a porous seabed is proposed, based on a multi-artificial neural network (MANN) method. Numerical results indicate that the MANN model can provide an accurate prediction of the wave-induced maximum liquefaction depth with 10% of the original database. This study demonstrates the capacity of the proposed MANN model and provides coastal engineers with another effective tool to analyse the stability of the marine sediment.
dc.description.peerreviewedYes
dc.description.publicationstatusYes
dc.format.extent551359 bytes
dc.format.mimetypeapplication/pdf
dc.languageEnglish
dc.language.isoeng
dc.publisherElsevier
dc.publisher.placeUnited Kingdom
dc.relation.ispartofstudentpublicationN
dc.relation.ispartofpagefrom878
dc.relation.ispartofpageto887
dc.relation.ispartofissue7
dc.relation.ispartofjournalOcean Engineering
dc.relation.ispartofvolume38
dc.rights.retentionY
dc.subject.fieldofresearchOceanography
dc.subject.fieldofresearchCivil engineering
dc.subject.fieldofresearchMaritime engineering
dc.subject.fieldofresearchMaritime engineering not elsewhere classified
dc.subject.fieldofresearchcode3708
dc.subject.fieldofresearchcode4005
dc.subject.fieldofresearchcode4015
dc.subject.fieldofresearchcode401599
dc.titlePrediction of maximum wave-induced liquefaction in porous seabed using multi-artificial neural network model
dc.typeJournal article
dc.type.descriptionC1 - Articles
dc.type.codeC - Journal Articles
gro.facultyGriffith Sciences, School of Engineering and Built Environment
gro.rights.copyright© 2010 Elsevier Inc. This is the author-manuscript version of this paper. Reproduced in accordance with the copyright policy of the publisher. Please refer to the journal's website for access to the definitive, published version.
gro.date.issued2011
gro.hasfulltextFull Text
gro.griffith.authorZhang, Hong


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