A Stacking Learning Model Based on Multiple Similar Days for Short-Term Load Forecasting

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...

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Autors principals:	Qi Jiang, Yuxin Cheng, Haozhe Le, Chunquan Li, Peter X. Liu
Format:	Article
Idioma:	English
Publicat:	MDPI AG 2022-07-01
Col·lecció:	Mathematics
Matèries:	short-term load forecasting (STLF) stacking ensemble learning similar-days forecasting sliding window broad learning system–backpropagation (BLS–BP)
Accés en línia:	https://www.mdpi.com/2227-7390/10/14/2446

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