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Real-time wave forecasting using genetic programming

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Field Value
 
Title Real-time wave forecasting using genetic programming
 
Creator GAUR, SURABHI
DEO, MC
 
Subject integer programming
computer programming
computer networks
forecasting
 
Description The forecasting of ocean waves on real-time or online basis is necessary while carrying out any operational activity in the ocean. In order to obtain forecasts that are station-specific a time-series-based approach like stochastic modeling or artificial neural network was attempted by some investigators in the past. This paper presents an application of a relatively new soft computing tool called genetic programming for this purpose. Genetic programming is an extension of genetic algorithm and it is suited to explore dependency between input and output data sets. The wave rider buoy measurements available at two locations in the Gulf of Mexico are analyzed. The forecasts of significant wave heights are made over lead times of 3, 6, 12 and 24 h. The sample size belonged to a period of 15 years and it included an extensive testing period of 5 years. The forecasts made by the approach of genetic programming indicated that it can be regarded as a promising tool for future applications to ocean predictions.
 
Publisher Elsevier
 
Date 2009-03-23T09:44:48Z
2011-11-25T20:17:58Z
2011-12-26T13:08:12Z
2011-12-27T05:56:12Z
2009-03-23T09:44:48Z
2011-11-25T20:17:58Z
2011-12-26T13:08:12Z
2011-12-27T05:56:12Z
2008
 
Type Article
 
Identifier Ocean Engineering 35(11-12), 1166-1172
0029-8018
http://dx.doi.org/10.1016/j.oceaneng.2008.04.007
http://hdl.handle.net/10054/1083
http://dspace.library.iitb.ac.in/xmlui/handle/10054/1083
 
Language en