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Simulated wave-driven ANN model for typhoon waves

dc.citation.epage34en_US
dc.citation.issue1-2en_US
dc.citation.spage25en_US
dc.citation.volume42en_US
dc.citation.woscount0
dc.contributor.authorChang, Hsien-Kuoen_US
dc.contributor.authorLiou, Jin-Chengen_US
dc.contributor.authorLiu, Shen-Jungen_US
dc.contributor.authorLiaw, Shyne-Rueyen_US
dc.contributor.department土木工程學系zh_TW
dc.contributor.departmentDepartment of Civil Engineeringen_US
dc.date.accessioned2014-12-08T15:37:46Z
dc.date.available2014-12-08T15:37:46Z
dc.date.issued2011-01-01en_US
dc.description.abstractThis paper investigates an artificial neural network (ANN) model for typhoon waves used to modify poor calculations of the numerical model in special cases. Two key factors, local winds and simulated waves produced by the numerical model, were used as input parameters of the proposed ANN model. The waves were simulated by the numerical model from a wave action equation indicating the physical processes of energy transfer and wave propagation. Simulated wave input is a very important parameter for the proposed ANN model, allowing for the accurate calculation of water waves in the sea. The applicable Mike21_SW model was chosen to provide an accurate calculation. Through model verification, the proposed ANN model has a particularly accurate calculation at the peak of each typhoon and at its occurrence time. The computed waves of each typhoon were examined to be consistent with the observed waves. (C) 2010 Elsevier Ltd. All rights reserved.en_US
dc.identifier.doi10.1016/j.advengsoft.2010.10.014en_US
dc.identifier.issn0965-9978en_US
dc.identifier.journalADVANCES IN ENGINEERING SOFTWAREen_US
dc.identifier.urihttp://dx.doi.org/10.1016/j.advengsoft.2010.10.014en_US
dc.identifier.urihttps://ir.lib.nycu.edu.tw/handle/11536/25966
dc.identifier.wosnumberWOS:000285534400003
dc.language.isoen_USen_US
dc.subjectMIKE21_SWen_US
dc.subjectArtificial neural networken_US
dc.subjectTyphoon wavesen_US
dc.subjectVortex wind modelen_US
dc.subjectNCEP wind fielden_US
dc.subjectHybrid wave modelen_US
dc.titleSimulated wave-driven ANN model for typhoon wavesen_US
dc.typeArticleen_US

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