Artificial Intelligent Systems and Machine Learning

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Neural Network for Ocean Wave Forecasting


Affiliations
1 Department of Applied Mechanics and Hydraulics, National Institute of Technology, Karnataka, Surathkal, 575025, India
2 Department of Applied Mechanics and Hydraulics, National Institute of Technology Karnataka, Surathkal, 575025, India
3 Center for Water Resources, Anna University, Chennai-600025, India
     

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Forecasting of wave parameters is necessary for many
marine and coastal operational related activities. In this paper, artificial neural network (ANN) as a robust data learning method is used to forecast the waveheight for the next 3hr, 6hr, 9hr, 12hr, 24hr, 48hr, 72hr, 96hr and 120hr in the Mangalore region, southwest coast of India. For this purpose two different models namely, Feed Forward Back Propagation (FFBP) and Nonlinear Auto Regressive Model with eXogenous input (NARX) of the ANN were used. The performances of developed models were evaluated using performance indices such as RMSE and CE. The CE values in FFBP model ranged from 0.997 to 0.785 while in NRAX model CE values are between 0.995 and 0.806 for the prediction time from 3hr to 120hr. A better agreement was observed between the observed and predicted waves for NRAX than that of FFBP for smaller (3-12hr) and larger lead period (24-120hr). Thus the NARX model performs better than the FFBP in terms of prediction capability and accuracy. 


Keywords

Waveheight, Prediction, ANN, FFBP, NRAX, RMSE.
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  • Neural Network for Ocean Wave Forecasting

Abstract Views: 224  |  PDF Views: 3

Authors

Gumageri Nagaraj
Department of Applied Mechanics and Hydraulics, National Institute of Technology, Karnataka, Surathkal, 575025, India
G. S. Dwarakish
Department of Applied Mechanics and Hydraulics, National Institute of Technology Karnataka, Surathkal, 575025, India
Sreenivasulu Dandagala
Department of Applied Mechanics and Hydraulics, National Institute of Technology Karnataka, Surathkal, 575025, India
Usha Natesan
Center for Water Resources, Anna University, Chennai-600025, India

Abstract


Forecasting of wave parameters is necessary for many
marine and coastal operational related activities. In this paper, artificial neural network (ANN) as a robust data learning method is used to forecast the waveheight for the next 3hr, 6hr, 9hr, 12hr, 24hr, 48hr, 72hr, 96hr and 120hr in the Mangalore region, southwest coast of India. For this purpose two different models namely, Feed Forward Back Propagation (FFBP) and Nonlinear Auto Regressive Model with eXogenous input (NARX) of the ANN were used. The performances of developed models were evaluated using performance indices such as RMSE and CE. The CE values in FFBP model ranged from 0.997 to 0.785 while in NRAX model CE values are between 0.995 and 0.806 for the prediction time from 3hr to 120hr. A better agreement was observed between the observed and predicted waves for NRAX than that of FFBP for smaller (3-12hr) and larger lead period (24-120hr). Thus the NARX model performs better than the FFBP in terms of prediction capability and accuracy. 


Keywords


Waveheight, Prediction, ANN, FFBP, NRAX, RMSE.