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    Recurrent networks for wave forecasting

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    Hydro_2002_260.pdf (444.3Kb)
    Date
    2002
    Author
    Mandal, S.
    Prabaharan, N.
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    Abstract
    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
    URI
    http://drs.nio.org/drs/handle/2264/1331
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