Pregled bibliografske jedinice broj: 760225
Deep neural networks for ultra-short-term wind forecasting
Deep neural networks for ultra-short-term wind forecasting // Proceedings of the 2015 IEEE International Conference on Industrial Technology (ICIT)
Sevilla, Španjolska, 2015. str. 1657-1663 doi:10.1109/ICIT.2015.7125335 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 760225 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Deep neural networks for ultra-short-term wind
forecasting
Autori
Đalto, Mladen ; Matuško, Jadranko ; Vašak, Mario
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
Proceedings of the 2015 IEEE International Conference on Industrial Technology (ICIT)
/ - , 2015, 1657-1663
Skup
International Conference on Industrial Technology
Mjesto i datum
Sevilla, Španjolska, 17.03.2015. - 19.03.2015
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
ultra-short-term ; wind ; prediction ; deep neural networks
Sažetak
The aim of this paper is to present input variable selection algorithm and deep neural networks application to ultrashort-term wind prediction. Shallow and deep neural networks coupled with input variable selection algorithm are compared on the ultra-short-term wind prediction task for a set of different locations. Results show that carefully selected deep neural networks outperform shallow ones. Input variable selection use reduces the neural network complexity and simplifies deep neural network training.
Izvorni jezik
Engleski
Znanstvena područja
Elektrotehnika
POVEZANOST RADA
Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb
