XgBoost based short-term electrical load forecasting considering trends & periodicity in historical data
author
Shabbir, Noman
Ahmadiahangar, Roya
Rosin, Argo
Jawad, Muhammad
Kilter, Jako
Martins, Joao
statement of authorship
Noman Shabbir, Roya Ahmadiahangar, Argo Rosin, Muhammad Jawad, Jako Kilter, Joao Martins
source
2023 IEEE International Conference on Energy Technologies for Future Grids (ETFG)
publisher
IEEE
year of publication
2023
pages
6 p
conference name, date
IEEE International Conference on Energy Technologies for Future Grids (ETFG), Dec. 3-6, 2023
conference location
Wollongong, Australia
url
https://doi.org/10.1109/ETFG55873.2023.10407926
subject term
elamud
elektrienergia
algoritmid
prognostika
elektrienergia
tehisõpe
Scopus
scopus
keyword
residential load
load forecast
machine learning (ML)
XgBoost algorithm
CAT boost
ISBN
978-166547164-0
notes
Bibliogr.: 25 ref
scientific publication
teaduspublikatsioon
classifier
3.1
TalTech department
elektroenergeetika ja mehhatroonika instituut
Targa linna tippkeskus
language
inglise
Reserch Group
Power systems research group
Microgrids and metrology