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...

Full beskrivning

Bibliografiska uppgifter
Huvudupphovsmän: Qi Jiang, Yuxin Cheng, Haozhe Le, Chunquan Li, Peter X. Liu
Materialtyp: Artikel
Språk:English
Publicerad: MDPI AG 2022-07-01
Serie:Mathematics
Ämnen:
short-term load forecasting (STLF)
stacking ensemble learning
similar-days forecasting
sliding window
broad learning system–backpropagation (BLS–BP)
Länkar:https://www.mdpi.com/2227-7390/10/14/2446

Internet

https://www.mdpi.com/2227-7390/10/14/2446

Liknande verk