scholarly journals Simultaneous short-term significant wave height and energy flux prediction using zonal multi-task evolutionary artificial neural networks

2021 ◽  
Author(s):  
A.M. Gómez-Orellana ◽  
D. Guijo-Rubio ◽  
P.A. Gutiérrez ◽  
C. Hervás-Martínez
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Wave Height ◽  
Energy Flux ◽  
Significant Wave Height ◽  
Short Term ◽  
Significant Wave ◽  
Artificial Neural

scholarly journals Prediction of the wave power in the Black Sea based on wind speed using artificial neural networks

2018 ◽  
Vol 51 ◽  
pp. 01006
Author(s):  
Sorin Ciortan ◽  
Eugen Rusu
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Wind Speed ◽  
Wave Height ◽  
Black Sea ◽  
Significant Wave Height ◽  
The Black Sea ◽  
Wave Power ◽  
Significant Wave ◽  
Artificial Neural

The paper proposes a prediction methodology for the significant wave height (and implicitly the wave power), based on the artificial neural networks. The proposed approach takes as input data the wind speed values recorded for different time periods. The prediction of significant wave height is useful both for assessment of wave energy as also for marine equipment design and navigation. The data used cover the time interval 1999 to 2007 and it was measured on Gloria drilling unit, which operates in the Romanian nearshore of the Black Sea at about 500 meters depth.

scholarly journals Prediction of the wave power in the Black Sea based on wind speed using artificial neural networks

2018 ◽  
Vol 51 ◽  
pp. 01006
Author(s):  
Sorin Ciortan ◽  
Eugen Rusu
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Wind Speed ◽  
Wave Height ◽  
Black Sea ◽  
Significant Wave Height ◽  
The Black Sea ◽  
Wave Power ◽  
Significant Wave ◽  
Artificial Neural

The paper proposes a prediction methodology for the significant wave height (and implicitly the wave power), based on the artificial neural networks. The proposed approach takes as input data the wind speed values recorded for different time periods. The prediction of significant wave height is useful both for assessment of wave energy as also for marine equipment design and navigation. The data used cover the time interval 1999 to 2007 and it was measured on Gloria drilling unit, which operates in the Romanian nearshore of the Black Sea at about 500 meters depth.

Short-term fading simulation using artificial neural networks

2011 ◽  
Vol 65 (7) ◽  
pp. 641-649 ◽  
Author(s):  
Nikola Tomasevic ◽  
Aleksandar Neskovic ◽  
Natasa Neskovic
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Short Term ◽  
Artificial Neural
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