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undergraduate thesis
Kratkoročno predviđanje cijene energenata upotrebom strojnog učenja
2017. urn:nbn:hr:168:189794
Podrebarac, David
University of Zagreb
Faculty of Electrical Engineering and Computing

Cite this document

Podrebarac, D. (2017). Kratkoročno predviđanje cijene energenata upotrebom strojnog učenja (Undergraduate thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:189794

Podrebarac, David. "Kratkoročno predviđanje cijene energenata upotrebom strojnog učenja." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2017. https://urn.nsk.hr/urn:nbn:hr:168:189794

Podrebarac, David. "Kratkoročno predviđanje cijene energenata upotrebom strojnog učenja." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2017. https://urn.nsk.hr/urn:nbn:hr:168:189794

Podrebarac, D. (2017). 'Kratkoročno predviđanje cijene energenata upotrebom strojnog učenja', Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 12 January 2025, https://urn.nsk.hr/urn:nbn:hr:168:189794

Podrebarac D. Kratkoročno predviđanje cijene energenata upotrebom strojnog učenja [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2017 [cited 2025 January 12] Available at: https://urn.nsk.hr/urn:nbn:hr:168:189794

D. Podrebarac, "Kratkoročno predviđanje cijene energenata upotrebom strojnog učenja", Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2017. Available at: https://urn.nsk.hr/urn:nbn:hr:168:189794

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Metadata
TitleKratkoročno predviđanje cijene energenata upotrebom strojnog učenja
Title (english)Short-term Energy-generating Product Price Forecasting Based on Machine Learning
AuthorDavid Podrebarac
MentorVladimir Čeperić (mentor)
Committee memberVladimir Čeperić (predsjednik povjerenstva)
Committee memberIvan Filković (član povjerenstva)
Committee memberMarko Magerl (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2017-07-10, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Ovaj rad fokusira se na kratkoročno predviđanje cijene sirove nafte upotrebom povratnih neuronskih mreža. Analizirano je nekoliko ulaznih značajki kao što su cijena zlata, indeks dolara i cijena loživog ulja. Implementirana je posebna vrsta povratnih neuronskih mreža, mreža s dugim kratkoročnim pamćenjem(engl. Long Short Term Memory, LSTM). Razne konfiguracije mreže su testirane kako bi se odredili optimalni hiperparametri. Dobiveni rezultati uspoređeni su sa sličnim znanstvenim radovima u literaturi.
Abstract (english)
This paper focuses on short term crude oil price forecasting using recurrent neural networks. Several input features were analized such as gold price, dollar index and heathing oil price. A special kind of recurrent neural networks, long short term memory (LSTM) network was implemented. Various model configurations were tested to determine the optimal hiperparameters. The model was compared with relevant models in the literature.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:189794
Study programmeTitle: Computing
Study programme type: university
Study level: undergraduate
Academic / professional title: sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva (sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
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Created on2019-03-14 00:04:00