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master's thesis
Neizrazita logika u analizi vremenskih sljedova
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2018. urn:nbn:hr:168:800255
Kolobara, Vinko
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

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Kolobara, V. (2018). Neizrazita logika u analizi vremenskih sljedova (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:800255

Kolobara, Vinko. "Neizrazita logika u analizi vremenskih sljedova." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2018. https://urn.nsk.hr/urn:nbn:hr:168:800255

Kolobara, Vinko. "Neizrazita logika u analizi vremenskih sljedova." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2018. https://urn.nsk.hr/urn:nbn:hr:168:800255

Kolobara, V. (2018). 'Neizrazita logika u analizi vremenskih sljedova', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 18 February 2025, https://urn.nsk.hr/urn:nbn:hr:168:800255

Kolobara V. Neizrazita logika u analizi vremenskih sljedova [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2018 [cited 2025 February 18] Available at: https://urn.nsk.hr/urn:nbn:hr:168:800255

V. Kolobara, "Neizrazita logika u analizi vremenskih sljedova", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2018. Available at: https://urn.nsk.hr/urn:nbn:hr:168:800255

Metadata
TitleNeizrazita logika u analizi vremenskih sljedova
Title (english)Fuzzy Logic for the Analysis of Time Sequences
AuthorVinko Kolobara
MentorDomagoj Jakobović (mentor)
Committee memberDomagoj Jakobović (predsjednik povjerenstva)
Committee memberAlan Jović (član povjerenstva)
Committee memberVlado Sruk (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2018-07-12, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Uobičajeni algoritmi analize financijskih vremenskih slijedova uglavnom su temeljeni na pravilima koja signaliziraju optimalno vrijeme ulaska ili izlaska iz pozicije u određenom slijedu. Zbog toga je korišten neizraziti sustav zaključivanja koji također omogućuje definiranje pravila pa i učenje istih uz neki algoritam strojnog učenja, tj. genetski algoritam. Uz primjenu na financijske vremenske slijedove, ispitana je sposobnost učenja neizrazitih pravila i na problemima klasifikacije i regresije. Za svaki od navedenih problema potrebno je definirati poseban genotip i evaluacijsku funkciju, a u slučaju regresije i poseban način kooperativne koevolucije. Analizira se uspješnost navedenih algoritama u usporedbi s već postojećim algoritmima specijaliziranih za te probleme.
Abstract (english)
The usual algorithms for the analysis of financial time series are mostly based on rules which signal the optimal time of entry or exit from a position in a specific financial series. Because of that, fuzzy inference system is used which allows for a similar definition of rules, and learning the same rules with a machine learning algorithm, genetic algorithm in this case. Beside the application on the financial time series, the ability of learning fuzzy rules for classification and regression is also tested. For each of the aforementioned problems, a specific genotype and evaluation function, or in the case of regression, even a special way of cooperative coevolution must be defined. The effectivenes of the algorithms is compared to the existing algorithms tailored for the problems.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:800255
Study programmeTitle: Computing
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra inženjer/inženjerka računarstva (magistar/magistra inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
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Created on2019-03-13 21:39:54