prikaz prve stranice dokumenta Prediktivni modeli potrošnje električne energije
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undergraduate thesis
Prediktivni modeli potrošnje električne energije
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2024. urn:nbn:hr:168:334332
Bubalo, Josip
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Bubalo, J. (2024). Prediktivni modeli potrošnje električne energije (Undergraduate thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:334332

Bubalo, Josip. "Prediktivni modeli potrošnje električne energije." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2024. https://urn.nsk.hr/urn:nbn:hr:168:334332

Bubalo, Josip. "Prediktivni modeli potrošnje električne energije." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2024. https://urn.nsk.hr/urn:nbn:hr:168:334332

Bubalo, J. (2024). 'Prediktivni modeli potrošnje električne energije', Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 17 November 2024, https://urn.nsk.hr/urn:nbn:hr:168:334332

Bubalo J. Prediktivni modeli potrošnje električne energije [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2024 [cited 2024 November 17] Available at: https://urn.nsk.hr/urn:nbn:hr:168:334332

J. Bubalo, "Prediktivni modeli potrošnje električne energije", Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2024. Available at: https://urn.nsk.hr/urn:nbn:hr:168:334332

Metadata
TitlePrediktivni modeli potrošnje električne energije
Title (english)
AuthorJosip Bubalo
MentorHrvoje Pandžić (mentor)
Committee memberHrvoje Pandžić (predsjednik povjerenstva)
Committee memberMateo Beus (član povjerenstva)
Committee memberJuraj Havelka (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2024-07-02, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Tema ovog rada je izrada prediktivnih modela strojnog učenja za potrošnju električne energije u kućanstvu. Nakon prikupljanja podataka nad njima je napravljena analiza u kojoj su otklonjene stršeće vrijednosti i popunjene rupe. S kompletiranim podatcima izrađeno je tri vrste modela predviđanja, osnovni baseline modeli, modeli linearne regresije i model slučajne šume. Na kraju, napravljena je usporedba uspješnosti predviđanja te tri vrste modela.
Abstract (english)
The topic of this thesis is the development of predictive machine learning models for household electricity consumption. After collecting the data, an analysis was made, in which outliers were removed and holes were filled. Three types of prediction models were created with the completed data: basic baseline models, linear regression models and random forest models. Finally, a comparison of the prediction performance of those three types of models was made.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:334332
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 20:12:55