prikaz prve stranice dokumenta Predviđanje budućih očitanja uređaja Interneta stvari putem dubokog učenja
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master's thesis
Predviđanje budućih očitanja uređaja Interneta stvari putem dubokog učenja
2022. urn:nbn:hr:168:261091
Kovačić, Stjepan
University of Zagreb
Faculty of Electrical Engineering and Computing

Cite this document

Kovačić, S. (2022). Predviđanje budućih očitanja uređaja Interneta stvari putem dubokog učenja (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:261091

Kovačić, Stjepan. "Predviđanje budućih očitanja uređaja Interneta stvari putem dubokog učenja." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. https://urn.nsk.hr/urn:nbn:hr:168:261091

Kovačić, Stjepan. "Predviđanje budućih očitanja uređaja Interneta stvari putem dubokog učenja." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. https://urn.nsk.hr/urn:nbn:hr:168:261091

Kovačić, S. (2022). 'Predviđanje budućih očitanja uređaja Interneta stvari putem dubokog učenja', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 27 February 2025, https://urn.nsk.hr/urn:nbn:hr:168:261091

Kovačić S. Predviđanje budućih očitanja uređaja Interneta stvari putem dubokog učenja [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2022 [cited 2025 February 27] Available at: https://urn.nsk.hr/urn:nbn:hr:168:261091

S. Kovačić, "Predviđanje budućih očitanja uređaja Interneta stvari putem dubokog učenja", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2022. Available at: https://urn.nsk.hr/urn:nbn:hr:168:261091

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Metadata
TitlePredviđanje budućih očitanja uređaja Interneta stvari putem dubokog učenja
Title (english)Predicting IoT Readings With Deep Learning
AuthorStjepan Kovačić
MentorVladimir Čeperić (mentor)
Committee memberVladimir Čeperić (predsjednik povjerenstva)
Committee memberMirko Poljak (član povjerenstva)
Committee memberTomislav Marković (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2022-07-15, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Tema ovog rada je primjena modela dubokog učenja na problem predviđanja budućih očitanja uređaja Interneta stvari. Objašnjeni su pojmovi Interneta stvari i dubokog učenja. Razvijen je LSTM model za predviđanje. Provedeni su postupci učenja modela i optimiranja hiperparametara. Predstavljeni su i analizirani rezultati razvijenog modela te su predložene moguće nadogradnje modela. Razvijeno je i predstavljeno programsko rješenje na odabranoj IoT platformi.
Abstract (english)
The subject of this thesis is the application of deep learning models for the problem of predicting IoT readings. The concepts of the Internet of Things and deep learning are explained. An LSTM model has been developed. Model training was performed as well as hyperparameter optimization. The results of the model are presented and analyzed. Possible model upgrades are proposed. IoT solution on the chosen IoT platform was developed and presented.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:261091
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
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Created on2023-01-14 09:09:57