Forecasting Day-Ahead Electricity Demand in Australia Using a CNN-LSTM Model with an Attention Mechanism

Accurate energy demand forecasting is vital for optimizing resource allocation and energy efficiency. Despite advancements in various prediction models, existing approaches often struggle to capture the complex, nonlinear relationships between temperature variations and electricity consumption. To a...

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Κύριοι συγγραφείς:	Laial Alsmadi, Gang Lei, Li Li
Μορφή:	Artigo
Γλώσσα:	Inglês
Έκδοση:	MDPI AG 2025-03-01
Σειρά:	Applied Sciences
Θέματα:	electricity demand prediction heating degree days cooling degree days deep learning Convolutional Neural Network (CNN)
Διαθέσιμο Online:	https://www.mdpi.com/2076-3417/15/7/3829
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