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undergraduate thesis
Predviđanje kretanja tržišta dionica neuronskim mrežama
2022. urn:nbn:hr:168:746092
Pavlović, Dario
University of Zagreb
Faculty of Electrical Engineering and Computing

Cite this document

Pavlović, D. (2022). Predviđanje kretanja tržišta dionica neuronskim mrežama (Undergraduate thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:746092

Pavlović, Dario. "Predviđanje kretanja tržišta dionica neuronskim mrežama." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. https://urn.nsk.hr/urn:nbn:hr:168:746092

Pavlović, Dario. "Predviđanje kretanja tržišta dionica neuronskim mrežama." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. https://urn.nsk.hr/urn:nbn:hr:168:746092

Pavlović, D. (2022). 'Predviđanje kretanja tržišta dionica neuronskim mrežama', Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 25 November 2024, https://urn.nsk.hr/urn:nbn:hr:168:746092

Pavlović D. Predviđanje kretanja tržišta dionica neuronskim mrežama [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2022 [cited 2024 November 25] Available at: https://urn.nsk.hr/urn:nbn:hr:168:746092

D. Pavlović, "Predviđanje kretanja tržišta dionica neuronskim mrežama", Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2022. Available at: https://urn.nsk.hr/urn:nbn:hr:168:746092

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Metadata
TitlePredviđanje kretanja tržišta dionica neuronskim mrežama
Title (english)Predicting stock prices using neural networks
AuthorDario Pavlović
MentorDomagoj Jakobović (mentor)
Committee memberDomagoj Jakobović (predsjednik povjerenstva)
Committee memberDavid Dukić (član povjerenstva)
Committee memberEda Jovičić (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2022-07-15, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
U radu je detaljnije objašnjen način funkcioniranja neuronskih mreža i njenih bitnih dijelova. Predstavljene su i povratne neuronske mreže, posebice vrsta povratne neuronske mreže – LSTM. Prikazana je i implementacija LSTM modela u svrhu predviđanja cijena dionica, zbog njegove karakteristike dobrog predviđanja vremenskog slijeda. Rezultati modela predviđanja su uglavnom nezadovoljavajući zbog vanjskih utjecaja i nasumičnosti čistih podataka o cijenama.
Abstract (english)
This thesis contains detailed explanation of neural networks and its important components. Recurrent neural networks are also elaborated in detail with emphasis on LSTM model. LSTM model is implemented for stock price prediction purposes because of its great time-series forecasting abilities. The results of the implemented model are mostly dissatisfying, because of external events and randomness of raw stock price data.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:746092
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 on2023-01-15 11:01:06