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Prediction of tides using back-propagation neural networks

DRS at CSIR-National Institute of Oceanography

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Title Prediction of tides using back-propagation neural networks
 
Creator Mandal, S.
 
Subject ocean tides
tidal prediction
offshore structures
harmonic analysis
tidal models
correlation analysis
 
Description Prediction of tides is very much essential for human activities and to reduce the construction cost in marine environment. This paper presents an application of the artificial neural network with back-propagation procedures for accurate prediction of tides. This neural network model predicts the time series data of hourly tides directly while using an efficient learning process called quickprop based on a previous set of data. Hourly tidal data measured at Gopalpur port - east coast of India was used for testing the back-propagation neural network model. Results show that the hourly data on tides for even a month can be predicted efficiently with a very high correlation coefficient (=0.9984).
 
Date 2009-01-07T11:01:37Z
2009-01-07T11:01:37Z
2001
 
Type Conference Article
 
Identifier International Conference in Ocean Engineering 2001, December 11-14, 2001, Silver Jubilee of the Department of Ocean Engineering. Proceedings, Vol.2; 499-504p.
http://drs.nio.org/drs/handle/2264/1606
 
Language en
 
Rights Copyright [2001]. All efforts have been made to respect the copyright to the best of our knowledge. Inadvertent omissions, if brought to our notice, stand for correction and withdrawal of document from this repository.
 
Publisher Allied, Chennai