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undergraduate thesis
Strojno učenje u predviđanju ponašanja nelinearnih sustava
2018. urn:nbn:hr:166:132577
Lokas, Ante
University of Split
Faculty of Science
Department of Informatics

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Lokas, A. (2018). Strojno učenje u predviđanju ponašanja nelinearnih sustava (Undergraduate thesis). Split: University of Split, Faculty of Science. Retrieved from https://urn.nsk.hr/urn:nbn:hr:166:132577

Lokas, Ante. "Strojno učenje u predviđanju ponašanja nelinearnih sustava." Undergraduate thesis, University of Split, Faculty of Science, 2018. https://urn.nsk.hr/urn:nbn:hr:166:132577

Lokas, Ante. "Strojno učenje u predviđanju ponašanja nelinearnih sustava." Undergraduate thesis, University of Split, Faculty of Science, 2018. https://urn.nsk.hr/urn:nbn:hr:166:132577

Lokas, A. (2018). 'Strojno učenje u predviđanju ponašanja nelinearnih sustava', Undergraduate thesis, University of Split, Faculty of Science, accessed 17 April 2024, https://urn.nsk.hr/urn:nbn:hr:166:132577

Lokas A. Strojno učenje u predviđanju ponašanja nelinearnih sustava [Undergraduate thesis]. Split: University of Split, Faculty of Science; 2018 [cited 2024 April 17] Available at: https://urn.nsk.hr/urn:nbn:hr:166:132577

A. Lokas, "Strojno učenje u predviđanju ponašanja nelinearnih sustava", Undergraduate thesis, University of Split, Faculty of Science, Split, 2018. Available at: https://urn.nsk.hr/urn:nbn:hr:166:132577

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Metadata
TitleStrojno učenje u predviđanju ponašanja nelinearnih sustava
Title (english)Machine learning in forcasting nonlinear systems
AuthorAnte Lokas
MentorSaša Mladenović (mentor)
Committee memberSaša Mladenović (predsjednik povjerenstva)
Committee memberDivna Krpan (član povjerenstva)
Committee memberGoran Zaharija (član povjerenstva)
GranterUniversity of Split
Faculty of Science
(Department of Informatics)
Split
Defense date and country2018-07-13, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Ovaj rad se bavi izradom ekonomskih predviđanja cijene na temelju podataka iz prošlosti putem umjetnih neuronskih mreža. Pojašnjeni su osnovni pojmovi teorije iz područja strojnog učenja, najviše umjetnih neuronskih mreža i ekonomije. Rad obuhvaća izradu vlastite umjetne neuronske mreže i testiranja s pravim povijesnim podacima s burze uz dokumentiran proces implementacije.
Abstract (english)
The paper deals with the description of the technologies that were needed to implement simple financial forecasting system that uses artificial neural networks. Theories and basic terms needed for understanding this paper from fields of economics, machine learning, mostly neural networks are explained. The paper involves projecting own artificial neural network model that uses real historical dana for making financial forecast. Process of implementing artificial neural network is documented and explained.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:166:132577
Study programmeTitle: Computer Science
Study programme type: university
Study level: undergraduate
Academic / professional title: sveučilišni/a prvostupnik/prvostupnica (baccalaureus/baccalaurea) informatike (sveučilišni/a prvostupnik/prvostupnica (baccalaureus/baccalaurea) informatike)
Type of resourceText
File originBorn digital
Access conditionsAccess restricted to students and staff of home institution
Terms of useLicence In copyright icon
Created on2019-01-28 15:08:07