Ocean wave forecasting using recurrent neural networks
DRS at CSIR-National Institute of Oceanography
View Archive InfoField | Value | |
Title |
Ocean wave forecasting using recurrent neural networks
|
|
Creator |
Mandal, S.
Prabaharan, N. |
|
Subject |
Wave forecasting
NARX recurrent network |
|
Description |
The tremendous increase in offshore operational activities demands improved waveforecasting 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 describes an artificial neural network, namely recurrent neural network with rprop update algorithm and is applied for wave forecasting. Measured ocean waves off Marmugao, west coast of India are used for this study. Here, the recurrent neural network 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 wave forecasting using recurrent neural network yields better results than the previous neural network application.
|
|
Date |
2006-06-27T06:42:30Z
2006-06-27T06:42:30Z 2006 |
|
Type |
Journal Article
|
|
Identifier |
Ocean Engineering 33 (10) 1401–1410p.
http://drs.nio.org/drs/handle/2264/155 |
|
Language |
en
|
|
Rights |
An edited version of this paper was published by Elsevier.
|
|
Format |
254998 bytes
application/pdf |
|
Publisher |
Elsevier
|
|