prikaz prve stranice dokumenta Algoritam diferencijalne evolucije za automatsko grupiranje podataka
  Download
PDF 124.26 KB
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

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

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

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

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 08 December 2024, https://urn.nsk.hr/urn:nbn:hr:200:986611

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 December 08] Available at: https://urn.nsk.hr/urn:nbn:hr:200:986611

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

Please login to the repository to save this object to your list.
Metadata
TitleAlgoritam diferencijalne evolucije za automatsko grupiranje podataka
Title (english)Differential evolution algorithm for automatic data clustering
AuthorKarlo Kotrba
MentorGoran Martinović (mentor)
MentorDražen Bajer (mentor)
Committee memberGoran Martinović (predsjednik povjerenstva)
Committee memberIvica Lukić (član povjerenstva)
Committee memberDražen Bajer (član povjerenstva)
GranterJosip 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 country2015-10-05, 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)
Languagecroatian
URN:NBNurn:nbn:hr:200:986611
Study programmeTitle: 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 resourceText
File originBorn digital
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2016-06-20 10:02:14