Show simple item record

dc.contributor.authorMandal, S.
dc.date.accessioned2007-07-26T05:49:37Z
dc.date.available2007-07-26T05:49:37Z
dc.date.issued2007
dc.identifier.citationOcean Engineering, vol.34(8-9), 1355-1356p.
dc.identifier.urihttp://drs.nio.org/drs/handle/2264/638
dc.description.abstractThe significant wave heights and periods are conventionally forecasted from the wind information on the basis of the wind–wave relationship. However, the error may become large due to many uncertainties in the wind generation prediction and wind–wave relationship. This is also confirmed by the authors, where the correlation (r) between measured wind speeds and significant wave heights is found to be 0.595 (r2 = 0.3541). The authors have rightly mentioned the restrictive uses of regression method (RM), especially for predicting wind-generated waves.
dc.format.extent73193 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.publisherElsevier
dc.rightsAn edited version of this paper was published by Elsevier. Copyright [2007] Elsevier
dc.subjectPerceptron Kalman filtering
dc.subjectArtificial neural network
dc.titleComments on ‘Temporal significant wave height estimation from wind speed by perceptron Kalman filtering’ by A. Altunkaynak and M. Ozger, Ocean Engineering, Vol. 31(10); 2004,1245-1255
dc.typeJournal Article


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record