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master's thesis
Strojno učenje u analizi AIS podataka
Rijeka: University of Rijeka, Faculty of Maritime Studies, Rijeka, 2022. urn:nbn:hr:187:995068
Doričić, Dominik
University of Rijeka
Faculty of Maritime Studies
Department of Marine Electronics and Communications

Institutional repository: Repository of the University of Rijeka, Faculty of Maritime Studies - FMSRI Repository

Cite this document

Doričić, D. (2022). Strojno učenje u analizi AIS podataka (Master's thesis). Rijeka: University of Rijeka, Faculty of Maritime Studies. Retrieved from https://urn.nsk.hr/urn:nbn:hr:187:995068

Doričić, Dominik. "Strojno učenje u analizi AIS podataka." Master's thesis, University of Rijeka, Faculty of Maritime Studies, 2022. https://urn.nsk.hr/urn:nbn:hr:187:995068

Doričić, Dominik. "Strojno učenje u analizi AIS podataka." Master's thesis, University of Rijeka, Faculty of Maritime Studies, 2022. https://urn.nsk.hr/urn:nbn:hr:187:995068

Doričić, D. (2022). 'Strojno učenje u analizi AIS podataka', Master's thesis, University of Rijeka, Faculty of Maritime Studies, accessed 02 December 2024, https://urn.nsk.hr/urn:nbn:hr:187:995068

Doričić D. Strojno učenje u analizi AIS podataka [Master's thesis]. Rijeka: University of Rijeka, Faculty of Maritime Studies; 2022 [cited 2024 December 02] Available at: https://urn.nsk.hr/urn:nbn:hr:187:995068

D. Doričić, "Strojno učenje u analizi AIS podataka", Master's thesis, University of Rijeka, Faculty of Maritime Studies, Rijeka, 2022. Available at: https://urn.nsk.hr/urn:nbn:hr:187:995068

Metadata
TitleStrojno učenje u analizi AIS podataka
Title (english)Machine learning in AISs data analysis
AuthorDominik Doričić
MentorIrena Jurdana (mentor)
MentorNikola Lopac (komentor)
Committee memberJasmin Ćelić (predsjednik povjerenstva)
Committee memberMarko Gulić (član povjerenstva)
GranterUniversity of Rijeka
Faculty of Maritime Studies
(Department of Marine Electronics and Communications)
Rijeka
Defense date and country2022-10-06, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Traffic and Transport Technology
Maritime and River Traffic
Abstract
U ovom radu obrađeno je korištenje podataka dobivenih Automatskim identifikacijskim sustavom (AIS) te primjena istih korištenjem strojnog učenja. Automatski identifikacijski sustav javlja statičke i dinamičke informacije plovila, koje su bitne za svijest o situaciji u pomorskom prometu. U radu su obrađene temeljne metode strojnog učenja. Strojno učenje grana je umjetne inteligencije koja se bave oblikovanjem algoritama koji svoju učinkovitost poboljšavaju na temelju empirijskih podataka. Danas je strojno učenje jedno od najaktivnijih i najuzbudljivijih područja računarske znanosti. Uz sve to prikazana je prednost korištenja strojnog učenja na podacima dobivenih iz AIS sustava.
Abstract (english)
This paper deals with the use of data obtained by the Automatic Identification System (AIS) and the application of these data using machine learning. The Automatic Identification System reports static and dynamic vessel information, which is essential for situational awareness in maritime transportation The paper deals with the fundamental methods of machine learning. machine learning is a branch of artificial intelligence that deals with designing algorithms that improve their efficiency based on empirical data. Today machine learning is one of the most active and exciting areas of computer science. In addition to all that, the advantage of using machine learning on the data obtained from the AIS system was shown.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:187:995068
Study programmeTitle: Marine Electronic Engineering and Information Technology - mag. ing. el.
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra inženjer/ inženjerka elektroničke i informatičke tehnologije (magistar/magistra inženjer/ inženjerka elektroničke i informatičke tehnologije)
Type of resourceText
File originBorn digital
Access conditionsAccess restricted to students and staff of home institution
Terms of useLicence In copyright icon
Created on2022-09-21 17:44:31