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Prediction of littoral drift with artificial neural networks

DSpace at IIT Bombay

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Title Prediction of littoral drift with artificial neural networks
 
Creator SINGH, AK
DEO, MC
KUMAR, VS
 
Subject sediment transport rate
water-level
models
wind
 
Description The amount of sand moving parallel to a coastline forms a prerequisite for many harbor design projects. Such information is currently obtained through various empirical formulae. Despite so many works in the past an accurate and reliable estimation of the rate of sand drift has still remained as a problem. The current study addresses this issue through the use of artificial neural networks (ANN). Feed forward networks were developed to predict the sand drift from a variety of causative variables. The best network was selected after trying out many alternatives. In order to improve the accuracy further its outcome was used to develop another network. Such simple two-stage training yielded most satisfactory results. An equation combining the network and a non-linear regression is presented for quick field usage. An attempt was made to see how both ANN and statistical regression differ in processing the input information. The network was validated by confirming its consistency with underlying physical process.
 
Publisher COPERNICUS PUBLICATIONS
 
Date 2011-07-20T11:04:04Z
2011-12-26T12:51:26Z
2011-12-27T05:36:32Z
2011-07-20T11:04:04Z
2011-12-26T12:51:26Z
2011-12-27T05:36:32Z
2008
 
Type Article
 
Identifier HYDROLOGY AND EARTH SYSTEM SCIENCES, 12(1), 267-275
1027-5606
http://dspace.library.iitb.ac.in/xmlui/handle/10054/5451
http://hdl.handle.net/10054/5451
 
Language en