prikaz prve stranice dokumenta Uporaba metoda strojnog učenja nad podacima vremenskih serija temperatura
No public access
master's thesis
Uporaba metoda strojnog učenja nad podacima vremenskih serija temperatura
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. urn:nbn:hr:168:574296
Marović, Ivan
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Marović, I. (2022). Uporaba metoda strojnog učenja nad podacima vremenskih serija temperatura (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:574296

Marović, Ivan. "Uporaba metoda strojnog učenja nad podacima vremenskih serija temperatura." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. https://urn.nsk.hr/urn:nbn:hr:168:574296

Marović, Ivan. "Uporaba metoda strojnog učenja nad podacima vremenskih serija temperatura." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. https://urn.nsk.hr/urn:nbn:hr:168:574296

Marović, I. (2022). 'Uporaba metoda strojnog učenja nad podacima vremenskih serija temperatura', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 03 November 2024, https://urn.nsk.hr/urn:nbn:hr:168:574296

Marović I. Uporaba metoda strojnog učenja nad podacima vremenskih serija temperatura [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2022 [cited 2024 November 03] Available at: https://urn.nsk.hr/urn:nbn:hr:168:574296

I. Marović, "Uporaba metoda strojnog učenja nad podacima vremenskih serija temperatura", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2022. Available at: https://urn.nsk.hr/urn:nbn:hr:168:574296

Metadata
TitleUporaba metoda strojnog učenja nad podacima vremenskih serija temperatura
Title (english)Using machine learning methods on temperature time series data
AuthorIvan Marović
MentorBoris Vrdoljak (mentor)
Committee memberBoris Vrdoljak (predsjednik povjerenstva)
Committee memberMirta Baranović (član povjerenstva)
Committee memberLjiljana Brkić (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2022-07-01, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
U radu se obrađuje korištenje metoda dubokog učenja kako bi se poboljšalo predviđanje temperature nekolicine meteoroloških web servisa temeljem povijesnih podataka tih web servisa. Podaci koji su korišteni u radu su vremenske serije, tako da se na početku rada govori o tome što su vremenske serije i na koje načine ih je moguće analizirati. Potom su opisane metode strojnog i dubokog učenja te matematička pozadina istih. Nakon toga su dodatno objašnjene podvrste neuronske mreže koje se mogu koristiti u dubokom učenju zvane povratne neuronske mreže, među kojima se nalazi i LSTM – poboljšanje nad radom običnih povratnih neuronskih mreža. Zatim je objašnjeno programsko rješenje modela te su prezentirani rezultati, da bi na kraju još bila prikazana korisnička aplikacija koja koristi napravljene modele.
Abstract (english)
This thesis examines how deep learning methods can be used for the improvement of temperature predictions of a few meteorological web services based on historic data of those web services. Time series data were used in model creation so the thesis first covers what time series are and in which way could they be analysed. Next, machine and deep learning methods are discussed. After that, the thesis focuses on recurrent neural networks among which is LSTM – an improvement over regular recurrent neural networks. Following that, the software solution is explained and the results are presented. Finally, a user application that uses models created in the software solution is presented.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:574296
Study programmeTitle: Computing
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra inženjer/inženjerka računarstva (magistar/magistra inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
Access conditionsClosed access
Terms of useLicence In copyright icon
Public note
Created on2023-01-13 13:01:17