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Pregled bibliografske jedinice broj: 1183565

A Comparison of Data-Driven Methods in Prediction of Weather Patterns in Central Croatia


Katušić, Damjan; Pripužić, Krešimir; Maradin, Mladen; Pripužić, Mirjana
A Comparison of Data-Driven Methods in Prediction of Weather Patterns in Central Croatia // Earth Science Informatics, 15 (2022), 1249-1265 doi:10.1007/s12145-022-00792-w (međunarodna recenzija, članak, znanstveni)


CROSBI ID: 1183565 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
A Comparison of Data-Driven Methods in Prediction of Weather Patterns in Central Croatia

Autori
Katušić, Damjan ; Pripužić, Krešimir ; Maradin, Mladen ; Pripužić, Mirjana

Izvornik
Earth Science Informatics (1865-0473) 15 (2022); 1249-1265

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

Ključne riječi
weather prediction ; climatology ; machine learning ; statistics

Sažetak
The prediction of future weather patterns has recently become a very important research area due to the ongoing climate change process which causes extreme weather events and rapidly changing weather patterns. In this paper we compare the prediction accuracy of eight data-driven methods, which had been developed for time series prediction, on future weather patterns in central Croatia. The evaluated methods are Seasonal na¨ıve, AutoRegressive Integrated Moving Average (ARIMA), Error-Trend-Seasonality (ETS), Exponential smoothing state space model with Box- Cox transformation (TBATS), Dynamic Harmonic Regression (DHR), Neural Network AutoRegression (NNAR), Support Vector Regression (SVR) and Long Short-Term Memory (LSTM). In our experimental evaluation, we use a historical data from 1961 to 2017 that contains temperature, air pressure and precipitation values for eight weather stations in central Croatia, and indices from two atmospheric oscillations, namely North Atlantic Oscillation (NAO) and Arctic Oscillation (AO). The results of our evaluation show that SVR is the best method, and that DHR and NNAR methods are also better than the other evaluated methods, as far as the accuracy of prediction is concerned. Among DHR and NNAR methods, DHR method is better for the prediction of temperature and air pressure, while NNAR method is better for the prediction of precipitation. Additionally, our evaluation shows that SVR, DHR and NNAR methods achieve a better prediction accuracy when oscillation indices are included as additional predictors.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika, Računarstvo, Geografija



POVEZANOST RADA


Projekti:
HRZZ-UIP-2017-05-9066 - Učinkovita stvarnovremenska obrada brzih geoprostornih podataka (RETROFIT) (Pripužić, Krešimir, HRZZ - 2017-05) ( POIROT)
EK-KF-KK.01.1.1.01.0009-1 - Napredne metode i tehnologije u znanosti o podatcima i kooperativnim sustavima - IJ za znanost o podatcima (Lončarić, Sven, EK - KK.01.1.1.01) ( POIROT)

Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb,
Prirodoslovno-matematički fakultet, Zagreb

Poveznice na cjeloviti tekst rada:

doi link.springer.com

Citiraj ovu publikaciju:

Katušić, Damjan; Pripužić, Krešimir; Maradin, Mladen; Pripužić, Mirjana
A Comparison of Data-Driven Methods in Prediction of Weather Patterns in Central Croatia // Earth Science Informatics, 15 (2022), 1249-1265 doi:10.1007/s12145-022-00792-w (međunarodna recenzija, članak, znanstveni)
Katušić, D., Pripužić, K., Maradin, M. & Pripužić, M. (2022) A Comparison of Data-Driven Methods in Prediction of Weather Patterns in Central Croatia. Earth Science Informatics, 15, 1249-1265 doi:10.1007/s12145-022-00792-w.
@article{article, author = {Katu\v{s}i\'{c}, Damjan and Pripu\v{z}i\'{c}, Kre\v{s}imir and Maradin, Mladen and Pripu\v{z}i\'{c}, Mirjana}, year = {2022}, pages = {1249-1265}, DOI = {10.1007/s12145-022-00792-w}, keywords = {weather prediction, climatology, machine learning, statistics}, journal = {Earth Science Informatics}, doi = {10.1007/s12145-022-00792-w}, volume = {15}, issn = {1865-0473}, title = {A Comparison of Data-Driven Methods in Prediction of Weather Patterns in Central Croatia}, keyword = {weather prediction, climatology, machine learning, statistics} }
@article{article, author = {Katu\v{s}i\'{c}, Damjan and Pripu\v{z}i\'{c}, Kre\v{s}imir and Maradin, Mladen and Pripu\v{z}i\'{c}, Mirjana}, year = {2022}, pages = {1249-1265}, DOI = {10.1007/s12145-022-00792-w}, keywords = {weather prediction, climatology, machine learning, statistics}, journal = {Earth Science Informatics}, doi = {10.1007/s12145-022-00792-w}, volume = {15}, issn = {1865-0473}, title = {A Comparison of Data-Driven Methods in Prediction of Weather Patterns in Central Croatia}, keyword = {weather prediction, climatology, machine learning, statistics} }

Časopis indeksira:


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


Citati:





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