A Stacking Learning Model Based on Multiple Similar Days for Short-Term Load Forecasting
It is challenging to obtain accurate and efficient predictions in short-term load forecasting (STLF) systems due to the complexity and nonlinearity of the electric load signals. To address these problems, we propose a hybrid predictive model that includes a sliding-window algorithm, a stacking ensem...
Główni autorzy: | , , , , |
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Format: | Artykuł |
Język: | English |
Wydane: |
MDPI AG
2022-07-01
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Seria: | Mathematics |
Hasła przedmiotowe: | |
Dostęp online: | https://www.mdpi.com/2227-7390/10/14/2446 |