Record Details

Recurrent networks for wave forecasting

DRS at CSIR-National Institute of Oceanography

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Field Value
 
Title Recurrent networks for wave forecasting
 
Creator Mandal, S.
Prabaharan, N.
 
Subject :wave propatation
wave data
offshore operations
wave height
surface water waves
 
Description The tremendous increase in offshore operational activities demands improved wave forecasting techniques. With the knowledge of accurate wave conditions, it is possible to carry out the marine activities such as offshore drilling, naval operations, merchant vessel routing, nearshore construction, etc. more efficiently and safely. This paper presents an application of the Artificial Neural Network, namely Backpropagation Recurrent Neural Network (BRNN) with rprop update algorithm for wave forecasting. Measured ocean waves off Marmugao, west coast of India are used for this study. Here, the BRNN of 3, 6 and 12 hourly wave forecasting yields the correlation coefficients of 0.95, 0.90 and 0.87 respectively. This shows that the BRNN with rprop algorithm gives good results. Wave forecasting using recurrent network yields much better results than the previous neural network application
 
Date 2008-08-02T11:37:55Z
2008-08-02T11:37:55Z
2002
 
Type Conference Article
 
Identifier Conference on Hydraulics, Water Resources and Ocean Engineering. Hydro 2002, December 16-17, 2002. (Conf. on Hydraulics, Water Resources and Ocean Engineering. Hydro 2002; IIT, Bombay; India; 16-17 Dec 2002). Indian Society for Hydraulics; Pune; India; 2002; 260-263p.
http://drs.nio.org/drs/handle/2264/1331
 
Language en
 
Publisher IIT, Bombay