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dc.contributor.authorSingh, A.K.
dc.contributor.authorDeo, M.C.
dc.contributor.authorSanilKumar, V.
dc.date.accessioned2008-01-31T04:43:36Z
dc.date.available2008-01-31T04:43:36Z
dc.date.issued2007
dc.identifier.citationProceedings of Institution of Civil Engineers - Maritime Enginerring, Vol.160; 113-119p.
dc.identifier.urihttp://drs.nio.org/drs/handle/2264/701
dc.description.abstractThe planning, operation, design and maintenance of almost all harbour and coastal engineering facilities call for an estimation of the longshore sediment transport rate. This is currently and popularly done with the help of empirical equations. In this paper an alternative approach based on a combination of two soft computing tools, namely neural networks and genetic programming, is suggested. Such a combination was found to produce better results than the individual use of neural networks or genetic programming. The ability of the neural network to approximate a non-linear function coupled with the efficiency of the genetic programming to make an optimum search over the solution domain seems to result in a better prediction.
dc.language.isoen
dc.publisherInstitution of Civil Engineers
dc.subjectsediment transport
dc.subjectlongshore sediment transport
dc.subjectcoastal engineering
dc.subjectharbours
dc.subjectcomputer programmes
dc.titleNeural network-genetic programming for sediment transport
dc.typeJournal Article


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