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An improved and explainable electricity price forecasting model via SHAP-based error compensation approach

author
Heistrene, Leena
Belikov, Juri
Baimel, Dmitry
Katzir, Liran
Machlev, Ram
Levy, Kfir
Mannor, Shie
Levron, Yoash
statement of authorship
Leena Heistrene, Juri Belikov, Dmitry Baimel, Liran Katzir, Ram Machlev, Kfir Levy
source
IEEE Transactions on Artificial Intelligence
publisher
IEEE
journal volume number month
vol. 6, 1
year of publication
2025
pages
p. 159-168
url
https://doi.org/10.1109/TAI.2024.3455313
subject term
elektrienergia
turuhinnad
tehisnärvivõrgud
tehisintellekt
tarkvara
keyword
convolutional neural network (CNN)
electricity price forecasting
explainable artificial intelligence
forecasting errors
long short-term memory (LSTM)
price spike
shapley additive explanations (SHAP)
XAI
XGBoost
ISSN
2691-4581
notes
Bibliogr.: 44 ref
scientific publication
teaduspublikatsioon
classifier
1.1
Scopus
Journal metrics at Scopus
Article at Scopus
category (general)
Computer science
category (sub)
Computer science. Computer science applications
Computer science. Artificial intelligence
TalTech department
tarkvarateaduse instituut
language
inglise
Heistrene, L., Belikov, J., Baimel, D., Katzir, L., Machlev, R., Levy, K., Mannor, S., Levron, Y. An improved and explainable electricity price forecasting model via SHAP-based error compensation approach // IEEE Transactions on Artificial Intelligence (2025) vol. 6, 1, p. 159-168. https://doi.org/10.1109/TAI.2024.3455313