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master's thesis
Procjena vjerojatnosti neželjenih događaja u mobilnim mrežama pomoću Bayesovih mreža
Osijek: Josip Juraj Strossmayer University of Osijek, Department of Mathematics, 2020. urn:nbn:hr:126:387618
Klobučar Markoš, Josipa
Josip Juraj Strossmayer University of Osijek
Department of Mathematics
Chair of Applied Mathematics and Computer Science
Applied Mathematics and Optimization Research Group

Institutional repository: Repository of School of Applied Mathematics and Computer Science

Cite this document

Klobučar Markoš, J. (2020). Procjena vjerojatnosti neželjenih događaja u mobilnim mrežama pomoću Bayesovih mreža (Master's thesis). Osijek: Josip Juraj Strossmayer University of Osijek, Department of Mathematics. Retrieved from https://urn.nsk.hr/urn:nbn:hr:126:387618

Klobučar Markoš, Josipa. "Procjena vjerojatnosti neželjenih događaja u mobilnim mrežama pomoću Bayesovih mreža." Master's thesis, Josip Juraj Strossmayer University of Osijek, Department of Mathematics, 2020. https://urn.nsk.hr/urn:nbn:hr:126:387618

Klobučar Markoš, Josipa. "Procjena vjerojatnosti neželjenih događaja u mobilnim mrežama pomoću Bayesovih mreža." Master's thesis, Josip Juraj Strossmayer University of Osijek, Department of Mathematics, 2020. https://urn.nsk.hr/urn:nbn:hr:126:387618

Klobučar Markoš, J. (2020). 'Procjena vjerojatnosti neželjenih događaja u mobilnim mrežama pomoću Bayesovih mreža', Master's thesis, Josip Juraj Strossmayer University of Osijek, Department of Mathematics, accessed 29 June 2024, https://urn.nsk.hr/urn:nbn:hr:126:387618

Klobučar Markoš J. Procjena vjerojatnosti neželjenih događaja u mobilnim mrežama pomoću Bayesovih mreža [Master's thesis]. Osijek: Josip Juraj Strossmayer University of Osijek, Department of Mathematics; 2020 [cited 2024 June 29] Available at: https://urn.nsk.hr/urn:nbn:hr:126:387618

J. Klobučar Markoš, "Procjena vjerojatnosti neželjenih događaja u mobilnim mrežama pomoću Bayesovih mreža", Master's thesis, Josip Juraj Strossmayer University of Osijek, Department of Mathematics, Osijek, 2020. Available at: https://urn.nsk.hr/urn:nbn:hr:126:387618

Metadata
TitleProcjena vjerojatnosti neželjenih događaja u mobilnim mrežama pomoću Bayesovih mreža
Title (english)Prediction of Faults in Cellular Network Using Bayesian Networks
AuthorJosipa Klobučar Markoš
MentorDarija Marković (mentor)
Committee memberDragana Jankov Maširević (predsjednik povjerenstva)
Committee memberDarija Marković (član povjerenstva)
Committee memberKristian Sabo (član povjerenstva)
GranterJosip Juraj Strossmayer University of Osijek
Department of Mathematics
(Chair of Applied Mathematics and Computer Science)
(Applied Mathematics and Optimization Research Group)
Osijek
Defense date and country2020-10-29, Croatia
Scientific / art field,
discipline and subdiscipline		NATURAL SCIENCES
Mathematics
Other Mathematical Disciplines
Abstract
Cilj ovog rada je upoznavanje s mogućnošću iskorištavanja prethodno pohranjenih događaja kako bi se procjenila vjerojatnost budućeg neželjenog događaja. Kvar mobilne mreže može se definirati kao nenormalan rad ili oštećenje na razini komponente, opreme ili podsustava, što znčajno umanjuje performanse aktivnog entiteta u mreži ili prekida komunikaciju. Sve pogreške (eng. error ) nisu kvar (eng. fault), jer ih protokoli uglavnom mogu riješiti. Kvar se može definirati kao nesposobnost predmeta da izvrši traženu funkciju (skup postupaka definiranih u svrhu postizanja odrđenog cilja), isključujući tu nemogućnost zbog preventivnog odžavanja, nedostatka vanjskih resursa ili planiranih aktivnosti. Kroz rad je prestavljen pristup ovom problemu pomoću Bayesovih mreža.
Abstract (english)
The aim of this paper is to introduce the possibility of using previously stored events to assess the probability of a future adverse event. Mobile network failure can be defined as abnormal operation or damage at the component, equipment or subsystem level, which significantly reduces the performance of an active entity in the network or interrupts communication. Not all errors are faults, as protocols can generally resolve them on their own. A failure can be defined as the inability of an object to perform a required function (a set of procedures defined in order to achieve a specific goal), excluding this inability due to preventive maintenance, lack of external resources or planned activities. An approach to this problem using Bayesian networks is presented in this paper.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:126:387618
Study programmeTitle: Mathematics; specializations in: Financial and Statistical Mathematics, Mathematics and Computer Science, Industrial and Applied Mathematics
Course: Financial and Statistical Mathematics
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra matematike (magistar/magistra matematike)
Type of resourceText
File originBorn digital
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2020-11-02 11:50:03