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DKUM
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Title:
Napovedovanje porabe električne energije z rekurentnimi nevronskimi mrežami : magistrsko delo
Authors:
ID
Kos, Urban
(Author)
ID
Karakatič, Sašo
(Mentor)
More about this mentor...
Files:
MAG_Kos_Urban_2020.pdf
(7,12 MB)
MD5: C50D4E8183550B0BB18AE99864FB3F85
PID:
20.500.12556/dkum/42f659af-3439-49ce-a8ce-560b12772cc4
Language:
Slovenian
Work type:
Master's thesis/paper
Typology:
2.09 - Master's Thesis
Organization:
FERI - Faculty of Electrical Engineering and Computer Science
Abstract:
Predvidevanje porabe električne energije predstavlja zelo pomemben člen v elektroenergetski industriji, saj lahko pripomore k optimizaciji proizvodnje. S pomočjo strojnega učenja, natančneje rekurentnih nevronskih mrež, je mogoče natančno napovedati električno energijo. Veliko vlogo pri napovedovanju igrajo kakovost in količina podatkov ter arhitektura in nastavitve nevronske mreže. V teoretičnem delu je podrobno opisana nevronska mreža in njeni osnovni gradniki, kjer je bilo največ pozornosti posvečene rekurentnim mrežam, praktični del pa prikazuje izvedbo eksperimenta napovedovanja porabe električne energije z rekurentnimi nevronskimi mrežami z različno arhitekturo in podatki.
Keywords:
rekurentne nevronske mreže
,
električna energija
,
napovedovanje električne energije
Place of publishing:
Maribor
Place of performance:
Maribor
Publisher:
[U. Kos]
Year of publishing:
2020
Number of pages:
XII, 124 str.
PID:
20.500.12556/DKUM-76195
UDC:
[004.832:519.216]:621.31(043.2)
COBISS.SI-ID:
27115523
NUK URN:
URN:SI:UM:DK:1MSOEKSP
Publication date in DKUM:
03.07.2020
Views:
1541
Downloads:
165
Metadata:
Categories:
KTFMB - FERI
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:
KOS, Urban, 2020,
Napovedovanje porabe električne energije z rekurentnimi nevronskimi mrežami : magistrsko delo
[online]. Master’s thesis. Maribor : U. Kos. [Accessed 2 April 2025]. Retrieved from: https://dk.um.si/IzpisGradiva.php?lang=eng&id=76195
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Licences
License:
CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Link:
http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:
The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Licensing start date:
22.04.2020
Secondary language
Language:
English
Title:
Predicting power consumption with recurrent neural networks
Abstract:
The anticipation of electricity consumption represents a very important link in the electrical energy industry as it can help optimize production. With the help of machine learning, more precisely recurrent neural networks, electricity can be accurately predicted. The quality and quantity of data, as well as the architecture and settings of the neural network play a big role in forecasting. The theoretical part describes in detail the neural network and its basic building blocks, where the greatest attention was paid to the recurrent parts of the network and the practical part shows the implementation of an experiment for the prediction of electricity consumption with recurrent neural networks with different architecture and data.
Keywords:
recurrent neural networks
,
electricity
,
electricity forecasting
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