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UHER, V. BURGET, R. DUTTA, M. MLÝNEK, P.
Originální název
Forecasting Electricity Consumption in Czech Republic
Typ
článek ve sborníku ve WoS nebo Scopus
Jazyk
angličtina
Originální abstrakt
Correct prediction of electricity consumption is important for planning its production in the short term, but also in the long term due to the construction of new power plants and mining planning. Accurate prediction is a challenging task because the consumption changes both in the day and during the whole year. The paper describes a method based only on input data for consumption. No additional influences were included such as temperature, wind, GDP (Gross Domestic Product). Five machine learning algorithms were used to create a predictive model. The best results were achieved with a local polynomial regression algorithm. Daily prediction error was 5.77%, weekly 3.49% and monthly 2.41%.
Klíčová slova
Electricity consumption, forecast, machine learning, optimalization, prediction
Autoři
UHER, V.; BURGET, R.; DUTTA, M.; MLÝNEK, P.
Rok RIV
2015
Vydáno
9. 7. 2015
Místo
Prague, Czech Republic
ISBN
978-1-4799-8497-8
Kniha
Proceedings of the 38th International Conference on Telecommunication and Signal Processing, TSP 2015
ISSN
NEUVEDENO
Strany od
262
Strany do
265
Strany počet
4
URL
https://ieeexplore.ieee.org/document/7296264
BibTex
@inproceedings{BUT115494, author="Václav {Uher} and Radim {Burget} and Malay Kishore {Dutta} and Petr {Mlýnek}", title="Forecasting Electricity Consumption in Czech Republic", booktitle="Proceedings of the 38th International Conference on Telecommunication and Signal Processing, TSP 2015", year="2015", pages="262--265", address="Prague, Czech Republic", doi="10.1109/TSP.2015.7296264", isbn="978-1-4799-8497-8", url="https://ieeexplore.ieee.org/document/7296264" }