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dc.contributor.authorLee, TL
dc.contributor.authorJeng, DS
dc.date.accessioned2017-05-03T11:58:50Z
dc.date.available2017-05-03T11:58:50Z
dc.date.issued2002
dc.date.modified2007-03-14T21:48:24Z
dc.identifier.issn0029-8018
dc.identifier.urihttp://hdl.handle.net/10072/6660
dc.description.abstractAn accurate tidal forecast is an important task in determining constructions and human activities in ocean environments. Conventional tidal forecasting has been based on harmonic analysis using the least squares method to determine harmonic parameters. However, a large number of parameters are required for the prediction of a long-term tidal level with harmonic analysis. Unlike conventional harmonic analysis, this paper presents an artificial neural network (ANN) model for forecasting the tidal-level using the short term measuring data. The ANN model can easily decide the unknown parameters by learning the input-output interrelation of the short-term tidal records. Three field data with three types of tides will be used to test the performance of the proposed ANN model. The numerical results indicate that the hourly tidal levels over a long duration can be predicted using a short-term hourly tidal record.
dc.description.peerreviewedYes
dc.description.publicationstatusYes
dc.languageEnglish
dc.language.isoeng
dc.publisherElsevier Science
dc.publisher.placeUK
dc.publisher.urihttp://www.elsevier.com/wps/find/journaldescription.cws_home/320/description#description
dc.relation.ispartofpagefrom1003
dc.relation.ispartofpageto1022
dc.relation.ispartofissue9
dc.relation.ispartofjournalOcean Engineering
dc.relation.ispartofvolume29
dc.subject.fieldofresearchOceanography
dc.subject.fieldofresearchCivil Engineering
dc.subject.fieldofresearchMaritime Engineering
dc.subject.fieldofresearchcode0405
dc.subject.fieldofresearchcode0905
dc.subject.fieldofresearchcode0911
dc.titleApplication of artificial neural networks for tide forecasting.
dc.typeJournal article
dc.type.descriptionC1 - Articles
dc.type.codeC - Journal Articles
gro.rights.copyright© 2002 Elsevier : Reproduced in accordance with the copyright policy of the publisher : This journal is available online - use hypertext links.
gro.date.issued2002
gro.hasfulltextNo Full Text
gro.griffith.authorJeng, Dong-Sheng


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