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...

詳細記述

書誌詳細
主要な著者: Qi Jiang, Yuxin Cheng, Haozhe Le, Chunquan Li, Peter X. Liu
フォーマット: 論文
言語:English
出版事項: MDPI AG 2022-07-01
シリーズ:Mathematics
主題:
short-term load forecasting (STLF)
stacking ensemble learning
similar-days forecasting
sliding window
broad learning system–backpropagation (BLS–BP)
オンライン･アクセス:https://www.mdpi.com/2227-7390/10/14/2446

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

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