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Predicting ocean surface currents using numerical weather prediction model and Kohonen neural network: a northern Adriatic study


Kalinić, Hrvoje; Mihanović, Hrvoje; Cosoli, Simone; Tudor, Martina; Vilibić, Ivica
Predicting ocean surface currents using numerical weather prediction model and Kohonen neural network: a northern Adriatic study // Neural computing & applications, 28 (2017), S1; 611-620 doi:10.1007/s00521-016-2395-4 (međunarodna recenzija, članak, znanstveni)


Naslov
Predicting ocean surface currents using numerical weather prediction model and Kohonen neural network: a northern Adriatic study

Autori
Kalinić, Hrvoje ; Mihanović, Hrvoje ; Cosoli, Simone ; Tudor, Martina ; Vilibić, Ivica

Izvornik
Neural computing & applications (0941-0643) 28 (2017), S1; 611-620

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
Self-organizing map Neural network Hybrid model Sea surface currents prediction

Sažetak
The paper documents a concept of ocean forecasting system for ocean surface currents based on self-organizing map (SOM) trained by high-resolution numerical weather prediction (NWP) model and high-frequency (HF) radar data. Wind and surface currents data from the northern Adriatic coastal area were used in a 6-month long training phase to obtain SOM patterns. Very high correlation between current and joined current and wind SOM patterns indicated the strong relationship between winds and currents and allowed for creation of a prediction system. Increasing SOM dimensions did not increase reliability of the forecasting system, being limited by the amount of the data used for training and achieving the lowest errors for 4 × 4 SOM matrix. As the HF radars and high-resolution NWP models are strongly expanding in coastal oceans, providing reliable and long-term datasets, the applicability of the proposed SOM-based forecasting system is expected to be high.

Izvorni jezik
Engleski

Znanstvena područja
Geologija



POVEZANOST RADA


Ustanove
Institut za oceanografiju i ribarstvo, Split,
Državni hidrometeorološki zavod,
Prirodoslovno-matematički fakultet, Split

Časopis indeksira:


  • Current Contents Connect (CCC)
  • Web of Science Core Collection (WoSCC)
    • Science Citation Index Expanded (SCI-EXP)
    • SCI-EXP, SSCI i/ili A&HCI
  • Scopus


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