Machine learning and deep learning techniques for residential load forecasting : a comparative analysis
author
Shabbir, Noman
Kütt, Lauri
Raja, Hadi Ashraf
Ahmadiahangar, Roya
Rosin, Argo
Husev, Oleksandr
statement of authorship
Noman Shabbir, Lauri Kütt, Hadi A. Raja, Roya Ahmadiahangar, Argo Rosin, Oleksandr Husev
source
2021 IEEE 62nd International Scientific Conference on Power and Electrical Engineering of Riga Technical University (RTUCON): conference proceedings
publisher
IEEE
year of publication
2021
pages
p. 1-5
conference name, date
IEEE 62nd International Scientific Conference on Power and Electrical Engineering of Riga Technical University (RTUCON), 15-17 November 2021
conference location
Riga, Latvia
url
https://doi.org/10.1109/RTUCON53541.2021.9711741
subject term
tehisõpe
sügavõpe
tehisnärvivõrgud
elanikud
koormus (tehnika)
prognostika
keyword
residential load
load forecasting
machine learning
deep learning
neural networks
ISBN
978-1-6654-3804-9
scientific publication
teaduspublikatsioon
classifier
3.1
TTÜ department
elektroenergeetika ja mehhatroonika instituut
language
inglise
Uurimisrühm
Electrical machines research group
Fundamentals of electrical engineering
Power electronics group
Microgrids and metrology
Smart city research group