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undergraduate thesis
Predviđanje cijena dionica zasnovano na modelima dubokog učenja
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2020. urn:nbn:hr:168:391609
Šikić Vagić, Matej
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Šikić Vagić, M. (2020). Predviđanje cijena dionica zasnovano na modelima dubokog učenja (Undergraduate thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:391609

Šikić Vagić, Matej. "Predviđanje cijena dionica zasnovano na modelima dubokog učenja." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2020. https://urn.nsk.hr/urn:nbn:hr:168:391609

Šikić Vagić, Matej. "Predviđanje cijena dionica zasnovano na modelima dubokog učenja." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2020. https://urn.nsk.hr/urn:nbn:hr:168:391609

Šikić Vagić, M. (2020). 'Predviđanje cijena dionica zasnovano na modelima dubokog učenja', Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 21 June 2024, https://urn.nsk.hr/urn:nbn:hr:168:391609

Šikić Vagić M. Predviđanje cijena dionica zasnovano na modelima dubokog učenja [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2020 [cited 2024 June 21] Available at: https://urn.nsk.hr/urn:nbn:hr:168:391609

M. Šikić Vagić, "Predviđanje cijena dionica zasnovano na modelima dubokog učenja", Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2020. Available at: https://urn.nsk.hr/urn:nbn:hr:168:391609

Metadata
TitlePredviđanje cijena dionica zasnovano na modelima dubokog učenja
Title (english)Prediction of Stock Market Prices Based on Deep Learning Models
AuthorMatej Šikić Vagić
MentorGoran Delač (mentor)
Committee memberGoran Delač (predsjednik povjerenstva)
Committee memberAdrian Satja Kurdija (član povjerenstva)
Committee memberLucija Šikić (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2020-09-07, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Rad obrađuje temu predviđanje cijena dionica zasnovano na modelima dubokog učenja, točnije koristi se mreža s dugom kratkotrajnom memorijom. Rad će se na početku osvrnuti i na povratne neuronske mreže kao roditelja mreže s dugom kratkotrajnom memorijom. Pomoću mreže s dugom kratkotrajnom memorijom može se predvidjeti rast ili pad neke dionice isključivo s prijašnjim cijenama spomenute dionice. Za ulazni skup informacija uzima se samo datum, cijena dionice na otvaranju i zatvaranju burze. Kasnije, nakon istraživanja trendova, izrađuje se model na setu za treniranje. Nakon raznih preinaka modela uz promjenu raznih parametara poput slučajnog izostavljanja nekih podataka te promjene broja mreža, provjerava se točnost modela na testnom setu podataka koji je odvojen od seta za treniranje.
Abstract (english)
The paper deals with the topic of stock price forecasting based on deep learning models, more precisely using a network with long short-term memory. The paper will initially look at reverse neural networks as the parent of a network with long short-term memory. With the help of a network with long short-term memory, it is possible to predict the growth or decline of a stock only with the previous prices of the mentioned stock. Only the date, share price at the opening and closing of the stock exchange is taken as the input set of information. Later, after researching the trends, a model is made on the training set. After various modifications of the model with a change of various parameters such as accidental omission of some data and a change in the number of networks, the accuracy of the model is checked on a test data set that is separate from the training set.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:391609
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 on2023-01-14 21:45:23