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Self-organizing maps-based ocean currents forecasting system
Vilibic, I.; Sepic, J.; Mihanovic, H.; Kalinic, H.; Cosoli, S.; Janekovic, I.; Žagar, N.; Jesenko, B.; Tudor, M.; Dadic, V.; Ivankovic, D. (2016). Self-organizing maps-based ocean currents forecasting system. NPG Scientific Reports 6(22924): 7 pp.
In: Scientific Reports (Nature Publishing Group). Nature Publishing Group: London. ISSN 2045-2322, more
Peer reviewed article  

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Authors  Top 
  • Vilibic, I.
  • Sepic, J.
  • Mihanovic, H.
  • Kalinic, H.
  • Cosoli, S.
  • Janekovic, I.
  • Žagar, N.
  • Jesenko, B.
  • Tudor, M.
  • Dadic, V., more
  • Ivankovic, D.

    An ocean surface currents forecasting system, based on a Self-Organizing Maps (SOM) neural network algorithm, high-frequency (HF) ocean radar measurements and numerical weather prediction (NWP) products, has been developed for a coastal area of the northern Adriatic and compared with operational ROMS-derived surface currents. The two systems differ significantly in architecture and algorithms, being based on either unsupervised learning techniques or ocean physics. To compare performance of the two methods, their forecasting skills were tested on independent datasets. The SOM-based forecasting system has a slightly better forecasting skill, especially during strong wind conditions, with potential for further improvement when data sets of higher quality and longer duration are used for training.

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