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undergraduate thesis
Mogućnosti primjene metoda strojnog učenja u području telekomunikacija
Zagreb: University of Zagreb, Faculty of Transport and Traffic Sciences, 2021. urn:nbn:hr:119:003361
Aleksić, David
University of Zagreb
Faculty of Transport and Traffic Sciences
Division of Transport
Department of Information and Communications Traffic

Institutional repository: Faculty of Transport and Traffic Sciences

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Aleksić, D. (2021). Mogućnosti primjene metoda strojnog učenja u području telekomunikacija (Undergraduate thesis). Zagreb: University of Zagreb, Faculty of Transport and Traffic Sciences. Retrieved from https://urn.nsk.hr/urn:nbn:hr:119:003361

Aleksić, David. "Mogućnosti primjene metoda strojnog učenja u području telekomunikacija." Undergraduate thesis, University of Zagreb, Faculty of Transport and Traffic Sciences, 2021. https://urn.nsk.hr/urn:nbn:hr:119:003361

Aleksić, David. "Mogućnosti primjene metoda strojnog učenja u području telekomunikacija." Undergraduate thesis, University of Zagreb, Faculty of Transport and Traffic Sciences, 2021. https://urn.nsk.hr/urn:nbn:hr:119:003361

Aleksić, D. (2021). 'Mogućnosti primjene metoda strojnog učenja u području telekomunikacija', Undergraduate thesis, University of Zagreb, Faculty of Transport and Traffic Sciences, accessed 03 October 2024, https://urn.nsk.hr/urn:nbn:hr:119:003361

Aleksić D. Mogućnosti primjene metoda strojnog učenja u području telekomunikacija [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Transport and Traffic Sciences; 2021 [cited 2024 October 03] Available at: https://urn.nsk.hr/urn:nbn:hr:119:003361

D. Aleksić, "Mogućnosti primjene metoda strojnog učenja u području telekomunikacija", Undergraduate thesis, University of Zagreb, Faculty of Transport and Traffic Sciences, Zagreb, 2021. Available at: https://urn.nsk.hr/urn:nbn:hr:119:003361

Metadata
TitleMogućnosti primjene metoda strojnog učenja u području telekomunikacija
Title (english)Opportunities for Applying Machine Learning Methods in Telecommunications
AuthorDavid Aleksić
MentorIvan Cvitić (mentor)
Committee memberDragan Peraković (predsjednik povjerenstva)
Committee memberSiniša Husnjak (član povjerenstva)
Committee memberMarko Periša (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Transport and Traffic Sciences
(Division of Transport)
(Department of Information and Communications Traffic)
Zagreb
Defense date and country2021-08-31, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Traffic and Transport Technology
Postal and Telecommunications Traffic
Abstract
Ovaj završni rad prikazuje metode strojnog učenja i mogućnosti primjene strojnog učenja u području telekomunikacija. Uz primjere primjene strojnog učenja također je definiran pojam umjetne inteligencije koja je danas u sve češćoj upotrebi u svijetu. Strojno učenje kao podsustav umjetne inteligencije ima veliki broj vlastitih algoritama koji se koriste za različite primjere. Sa sve većim razvojem tehnologija kao što su veće brzine interneta, 5G mobilne mreže itd. iz npr. telekomunikacijskog područja dolazi do potrebe za boljim upravljanjem i podrškom za sustave koji se koriste novim tehnologijama. Metode strojnog učenja mogu se koristiti za poboljšanje korisničke usluge prikupljanjem podataka, za prikupljanje podataka o prometu u mreži i općenito u svim sustavima u kojima se zahtjeva prikupljanje, grupiranje i analiza podataka.
Abstract (english)
This bachelor's thesis shows methods of machine learning and opportunities of using it in telecommunications. With the examples of using machine learning methods, the term of artificial intelligence, which is today used more than ever before, is defined in this thesis as well. Machine learning as a subset of artificial intelligence has a lot of its own algorithms and methods. With the improvement of the new technologies such as higher internet speeds, 5G mobile networks etc. for e.g., in telecommunication, comes the need for the new and improved management and support for the systems that are using those new technologies. Some types of machine learning can be used for collecting data to improve user’s quality of service, some are used for collecting data of traffic in networks or generally for any system that has the need to collect data, cluster data points and analysing data.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:119:003361
Study programmeTitle: Traffic and Transport; specializations in: Road Traffic and Transport, Railway Traffic and Transport, Water Traffic and Transport, Air Traffic and Transport, Postal Traffic, Information and Communication Traffic, Urban Traffic and Transport
Course: Road Traffic and Transport
Study programme type: university
Study level: undergraduate
Academic / professional title: sveučilišni/a prvostupnik/prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka prometa (sveučilišni/a prvostupnik/prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka prometa)
Type of resourceText
File originBorn digital
Access conditionsOpen access
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Created on2021-09-03 14:08:11