Show simple item record

dc.contributor.authorMandal, S.
dc.contributor.authorPrabaharan, N.
dc.date.accessioned2006-06-27T06:42:30Z
dc.date.available2006-06-27T06:42:30Z
dc.date.issued2006
dc.identifier.citationOcean Engineering 33 (10) 1401–1410p.
dc.identifier.urihttp://drs.nio.org/drs/handle/2264/155
dc.description.abstractThe tremendous increase in offshore operational activities demands improved waveforecasting techniques. With the knowledge of accurate wave conditions, it is possible to carry out the marine activities such as offshore drilling, naval operations, merchant vessel routing, nearshore construction, etc. more efficiently and safely. This paper describes an artificial neural network, namely recurrent neural network with rprop update algorithm and is applied for wave forecasting. Measured ocean waves off Marmugao, west coast of India are used for this study. Here, the recurrent neural network of 3, 6 and 12 hourly wave forecasting yields the correlation coefficients of 0.95, 0.90 and 0.87 respectively. This shows that the wave forecasting using recurrent neural network yields better results than the previous neural network application.
dc.format.extent254998 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.publisherElsevier
dc.rightsAn edited version of this paper was published by Elsevier.
dc.subjectWave forecasting
dc.subjectNARX recurrent network
dc.titleOcean wave forecasting using recurrent neural networks
dc.typeJournal Article


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record