prikaz prve stranice dokumenta Istraživanje asteroida primjenom algoritama grupiranja u strojnom učenju
  Download
PDF 2.9 MB
master's thesis
Istraživanje asteroida primjenom algoritama grupiranja u strojnom učenju
Zagreb: University of Zagreb, Faculty of Science, 2017. urn:nbn:hr:217:058781
Đunđek, Vedrana
University of Zagreb
Faculty of Science
Department of Physics

Institutional repository: Repository of the Faculty of Science

Cite this document

Đunđek, V. (2017). Istraživanje asteroida primjenom algoritama grupiranja u strojnom učenju (Master's thesis). Zagreb: University of Zagreb, Faculty of Science. Retrieved from https://urn.nsk.hr/urn:nbn:hr:217:058781

Đunđek, Vedrana. "Istraživanje asteroida primjenom algoritama grupiranja u strojnom učenju." Master's thesis, University of Zagreb, Faculty of Science, 2017. https://urn.nsk.hr/urn:nbn:hr:217:058781

Đunđek, Vedrana. "Istraživanje asteroida primjenom algoritama grupiranja u strojnom učenju." Master's thesis, University of Zagreb, Faculty of Science, 2017. https://urn.nsk.hr/urn:nbn:hr:217:058781

Đunđek, V. (2017). 'Istraživanje asteroida primjenom algoritama grupiranja u strojnom učenju', Master's thesis, University of Zagreb, Faculty of Science, accessed 23 December 2024, https://urn.nsk.hr/urn:nbn:hr:217:058781

Đunđek V. Istraživanje asteroida primjenom algoritama grupiranja u strojnom učenju [Master's thesis]. Zagreb: University of Zagreb, Faculty of Science; 2017 [cited 2024 December 23] Available at: https://urn.nsk.hr/urn:nbn:hr:217:058781

V. Đunđek, "Istraživanje asteroida primjenom algoritama grupiranja u strojnom učenju", Master's thesis, University of Zagreb, Faculty of Science, Zagreb, 2017. Available at: https://urn.nsk.hr/urn:nbn:hr:217:058781

Metadata
TitleIstraživanje asteroida primjenom algoritama grupiranja u strojnom učenju
Title (english)The application of machine learning clustering algorithms to the study of asteroids
AuthorVedrana Đunđek
MentorGoranka Bilalbegović (mentor)
Committee memberGoranka Bilalbegović (predsjednik povjerenstva)
Committee memberDavor Horvatić (član povjerenstva)
Committee memberMihael Makek (član povjerenstva)
Committee memberKrešimir Kumerički (član povjerenstva)
Committee memberŽeljko Skoko (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Science
(Department of Physics)
Zagreb
Defense date and country2017-08-30, Croatia
Scientific / art field,
discipline and subdiscipline		NATURAL SCIENCES
Physics
Abstract
S napretkom teleskopa i razvojem algoritama strojnog učenja povećava se mogućnost uočavanja novih asteroida i određivanja njihovih osobina. U ovom diplomskom radu analizirani su asteroidi u blizini Zemlje pomoću nenadziranog strojnog učenja. Koristili smo dva algoritama grupiranja u programskom jeziku Python: KMEANS i DBSCAN. Pokušali smo grupirati asteroide u blizini Zemlje koristeći podatke američke državne uprave za zrakoplovna i svemirska istraživanja (NASA). Usporedili smo rezultate s poznatim potencijalno opasnim asteroidima. Trenutne verzije korištenih programa dostupne su na adresi https://github.com/lib686/avenge-the-dinosaurs. Opisan je projekt znanosti za građanstvo Asteroids@home kao metodički dio diplomskog rada. Diskutiran je značaj ovog projekta za popularizaciju astronomije, informatike te znanosti općenito.
Abstract (english)
With the advancement of telescopes and the development of machine learning algorithms we increase the ability to detect new asteroids and determine their characteristics. In this master’s degree thesis, Near-Earth Asteroids (NEAs) were analyzed using unsupervised machine learning. We were using two clustering algorithms in programming language Python: KMEANS and DBSCAN. We attempted to cluster NEAs using data from National Aeronautics and Space Administration (NASA). We compared the results with known Potentially Hazardous Asteroids (PHA). Current versions of the programs used can be found at https://github.com/lib686/ avenge-the-dinosaurs. We described the citizen science project Asteroids@home as a teaching method part of the thesis. The importance of this project for the popularization of astronomy, computer science, and science in general is discussed.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:217:058781
Study programmeTitle: Physics and Computer Science; specializations in: Education
Course: Education
Study programme type: university
Study level: integrated undergraduate and graduate
Academic / professional title: magistar/magistra fizike i informatike (magistar/magistra fizike i informatike)
Type of resourceText
File originBorn digital
Access conditionsOpen access
Embargo expiration date: 2018-08-30
Terms of useLicence In copyright icon
Created on2017-09-13 11:19:25