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undergraduate thesis
Otkrivanje anomalija u vremenskim nizovima
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2024. urn:nbn:hr:168:262011
Udovičić, Josipa
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

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Udovičić, J. (2024). Otkrivanje anomalija u vremenskim nizovima (Undergraduate thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:262011

Udovičić, Josipa. "Otkrivanje anomalija u vremenskim nizovima." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2024. https://urn.nsk.hr/urn:nbn:hr:168:262011

Udovičić, Josipa. "Otkrivanje anomalija u vremenskim nizovima." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2024. https://urn.nsk.hr/urn:nbn:hr:168:262011

Udovičić, J. (2024). 'Otkrivanje anomalija u vremenskim nizovima', Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 26 December 2024, https://urn.nsk.hr/urn:nbn:hr:168:262011

Udovičić J. Otkrivanje anomalija u vremenskim nizovima [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2024 [cited 2024 December 26] Available at: https://urn.nsk.hr/urn:nbn:hr:168:262011

J. Udovičić, "Otkrivanje anomalija u vremenskim nizovima", Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2024. Available at: https://urn.nsk.hr/urn:nbn:hr:168:262011

Metadata
TitleOtkrivanje anomalija u vremenskim nizovima
Title (english)Time Series Anomaly Detection
AuthorJosipa Udovičić
MentorAdrian Satja Kurdija (mentor)
Committee memberAdrian Satja Kurdija (predsjednik povjerenstva)
Committee memberAnja Delić (član povjerenstva)
Committee memberDavid Dukić (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2024-07-08, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Ovaj rad istražuje metode za otkrivanje anomalija u vremenskim nizovima, s posebnim naglaskom na vremenske podatke poput temperature i padalina. Primjenom različitih algoritama, uključujući 𝜇 ±3𝜎, box plot pravilo i Grubbsov test (z-score), analizirana je njihova učinkovitost i točnost u identifikaciji anomalija. Eksperimentalni rezultati pokazuju da su algoritmi uspješno identificirali anomalije, iako se njihova točnost razlikovala ovisno o kvaliteti podataka i duljini vremenskog razdoblja. Korištenjem ADTK alata omogućena je fleksibilnost u detekciji anomalija, pružajući vrijedne uvide u sezonske i druge obrasce. Ovaj rad doprinosi razumijevanju metodologija za otkrivanje anomalija te može poslužiti kao osnova za daljnja istraživanja u ovom području.
Abstract (english)
This study investigates methods for anomaly detection in time series, with a particular focus on weather data such as temperature and precipitation. By applying various algorithms, including 𝜇 ± 3𝜎, box plot rule, and Grubbs’ test (z-score), their effectiveness and accuracy in identifying anomalies were analyzed. Experimental results show that the algorithms successfully identified anomalies, although their accuracy varied depending on the data quality and the length of the time period. The use of the ADTK tool provided flexibility in anomaly detection, offering valuable insights into seasonal and other patterns. This study contributes to the understanding of anomaly detection methodologies and can serve as a foundation for further research in this field.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:262011
Study programmeTitle: Computing
Study programme type: university
Study level: undergraduate
Academic / professional title: sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva (sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
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Created on2024-10-12 22:23:15