Applied Energy, Journal Year: 2024, Volume and Issue: 377, P. 124442 - 124442
Published: Sept. 19, 2024
Language: Английский
Applied Energy, Journal Year: 2024, Volume and Issue: 377, P. 124442 - 124442
Published: Sept. 19, 2024
Language: Английский
Energy and Buildings, Journal Year: 2025, Volume and Issue: unknown, P. 115404 - 115404
Published: Feb. 1, 2025
Language: Английский
Citations
0Building and Environment, Journal Year: 2025, Volume and Issue: unknown, P. 112693 - 112693
Published: Feb. 1, 2025
Language: Английский
Citations
0Elsevier eBooks, Journal Year: 2025, Volume and Issue: unknown
Published: Jan. 1, 2025
Language: Английский
Citations
0Journal of Building Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 112344 - 112344
Published: March 1, 2025
Language: Английский
Citations
0International Journal of Refrigeration, Journal Year: 2025, Volume and Issue: unknown
Published: April 1, 2025
Language: Английский
Citations
0International Journal of Dynamics and Control, Journal Year: 2025, Volume and Issue: 13(5)
Published: April 26, 2025
Language: Английский
Citations
0Journal of Building Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 112542 - 112542
Published: April 1, 2025
Language: Английский
Citations
0Journal of Building Performance Simulation, Journal Year: 2024, Volume and Issue: 17(5), P. 563 - 584
Published: June 12, 2024
Accurate heat load prediction is the key to ensure stable operation of thermal system and effective planning resources. However, current forecasting methods tend treat individual buildings as isolated entities, ignoring temporal spatial correlation between buildings. In this study, we propose a data-driven model based on spatiotemporal coupling predict short-term load. Firstly, among features various are analyzed by using autocorrelation function Spearman coefficient. Secondly, synchronous wavelet transform used eliminate high frequency noise characteristics building extracted improved Informer which concerned with multi-scale graphs. The experimental results show that proposed has better predictive performance than baseline model. It provides reference for accurate regulation system.
Language: Английский
Citations
1International Journal of Refrigeration, Journal Year: 2024, Volume and Issue: 167, P. 70 - 89
Published: July 23, 2024
Language: Английский
Citations
1Applied Energy, Journal Year: 2024, Volume and Issue: 377, P. 124442 - 124442
Published: Sept. 19, 2024
Language: Английский
Citations
0