Integration of Ensemble GoogLeNet and Modified Deep Residual Networks for Short-Term Load Forecasting

Due to the strong volatility of the electrical load and the defect of a time-consuming problem, in addition to overfitting existing in published forecasting methods, short-term electrical demand is difficult to forecast accurately and robustly. Given the excellent capability of weight sharing and fe...

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Veröffentlicht in:	Electronics (Basel) 2021-10, Vol.10 (20), p.2455
Hauptverfasser:	Ding, Aijia, Liu, Tingzhang, Zou, Xue
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Alternative energy sources Artificial intelligence Correlation analysis Economic forecasting Electrical loads Energy consumption Feature extraction Forecasting Machine learning Mathematical models Methods Neural networks Power Time series
Online-Zugang:	Volltext
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