Hybrid Attention-Based LSTM and XGBoost Model for Short-Term Residential Load Forecasting
statement of authorship
Noman Shabbir, Arqum Shahid, Kamran Daniel, Muhammad Jawad, Argo Rosin, Joao Martins
source
2025 IEEE the 13th International Conference on Smart Energy Grid Engineering (SEGE 2025)
location of publication
Piscataway
publisher
year of publication
pages
p. 94-99
conference name, date
IEEE the 13th International Conference on Smart Energy Grid Engineering (SEGE 2025) 18-20 August
conference location
Oshawa, Canada
ISBN
979-833158592-1
notes
Bibliogr.: 13 ref
scientific publication
teaduspublikatsioon
TalTech department
language
English
subject term
keyword
Scopus
classifier
Shabbir, N., Shahid, A., Daniel, K., Jawad, M., Rosin, A., Martins, J. Hybrid Attention-Based LSTM and XGBoost Model for Short-Term Residential Load Forecasting // 2025 IEEE the 13th International Conference on Smart Energy Grid Engineering (SEGE 2025). Piscataway : IEEE, 2025. p. 94-99.