Algoritam diferencijalne evolucije za automatsko grupiranje podataka

Kotrba, Karlo

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master's thesis

Algoritam diferencijalne evolucije za automatsko grupiranje podataka

2015. urn:nbn:hr:200:986611

Kotrba, Karlo

Josip Juraj Strossmayer University of Osijek
Faculty of Electrical Engineering, Computer Science and Information Technology Osijek
Department of Software Engineering
Chair of Programming Languages and Systems

Cite this document

APA 6th Edition

Kotrba, K. (2015). Algoritam diferencijalne evolucije za automatsko grupiranje podataka (Master's thesis). Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek. Retrieved from https://urn.nsk.hr/urn:nbn:hr:200:986611

MLA 8th Edition

Kotrba, Karlo. "Algoritam diferencijalne evolucije za automatsko grupiranje podataka." Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, 2015. https://urn.nsk.hr/urn:nbn:hr:200:986611

Chicago 17th Edition

Harvard

Kotrba, K. (2015). 'Algoritam diferencijalne evolucije za automatsko grupiranje podataka', Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, accessed 19 April 2024, https://urn.nsk.hr/urn:nbn:hr:200:986611

Vancouver

Kotrba K. Algoritam diferencijalne evolucije za automatsko grupiranje podataka [Master's thesis]. Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek; 2015 [cited 2024 April 19] Available at: https://urn.nsk.hr/urn:nbn:hr:200:986611

IEEE

K. Kotrba, "Algoritam diferencijalne evolucije za automatsko grupiranje podataka", Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, Osijek, 2015. Available at: https://urn.nsk.hr/urn:nbn:hr:200:986611

Cite this item: https://urn.nsk.hr/urn:nbn:hr:200:986611

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Metadata

Title	Algoritam diferencijalne evolucije za automatsko grupiranje podataka
Title (english)	Differential evolution algorithm for automatic data clustering
Author	Karlo Kotrba
Mentor	Goran Martinović (mentor)
Mentor	Dražen Bajer (mentor)
Committee member	Goran Martinović (predsjednik povjerenstva)
Committee member	Ivica Lukić (član povjerenstva)
Committee member	Dražen Bajer (član povjerenstva)
Granter	Josip Juraj Strossmayer University of Osijek Faculty of Electrical Engineering, Computer Science and Information Technology Osijek (Department of Software Engineering) (Chair of Programming Languages and Systems) Osijek
Defense date and country	2015-10-05, Croatia
Scientific / art field, discipline and subdiscipline	TECHNICAL SCIENCES Computing Process Computing
Abstract	Diplomski rad obrađuje uvod u algoritme za grupiranje podataka. Ukratko su obrađeni glavni tipovi algoritama, te načini vrednovanja kvalitete particije. Detaljnije je objašnjena diferencijalna evolucija uz povezivanje sa evolucijskim algoritmima. Prikazani su načini primjene diferencijalne evolucije pri grupiranju podataka u poznat ili nepoznat broj grupa. Također je opisan način pronalaženja odgovarajućeg broja grupa ukoliko on nije unaprijed poznat. Izrađeno je programsko rješenje koje omogućuje usporedbu raznih načina vrednovanja kvalitete grupiranja. Također je provedena eksperimentalna analiza gdje su prikazani i komentirani rezultati usporedbe. Uz ovo analizirana je i efikasnost raznih načina paraleliziranja programskog koda.
Abstract (english)	The thesis gives an introduction to data clustering algorithms. Main types of data clustering algorithms as well as different clustering validity criteria were described. Differential evolution and its application related to data clustering was described in detail. The applicability of differential evolution for automatic clustering as well as clustering when the number of clusters is known in advance was shown. Automatic clustering was described in depth. Software solution that enables a comparison between different clustering validity criteria was developed. The results of the aforementioned comparison were shown and commented. Efficacy analysis of multiple implementations of parallelism was also shown.
Keywords
Keywords (english)
Language	croatian
URN:NBN	urn:nbn:hr:200:986611
Study programme	Title: Graduate University Study Programme in Computer Engineering Study programme type: university Study level: graduate Academic / professional title: magistar/magistra inženjer/inženjerka računarstva (magistar/magistra inženjer/inženjerka računarstva)
Type of resource	Text
File origin	Born digital
Access conditions	Open access
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Created on	2016-06-20 10:02:14