Hybrid model for robust and accurate forecasting building electricity demand combining physical and data-driven methods

The high-precision prediction of building electrical demand is paramount significance for optimal control of building systems and the reduction of operational energy consumption. The pure physical simulation software struggles to depict buildings' energy usage behavior accurately; while purely...

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Vydané v:	Energy (Oxford) Ročník 311; s. 133309
Hlavní autori:	Dong, Xianzhou, Guo, Weiyong, Zhou, Cheng, Luo, Yongqiang, Tian, Zhiyong, Zhang, Limao, Wu, Xiaoying, Liu, Baobing
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier Ltd 01.12.2024
Predmet:	algorithms computer simulation Deep learning electricity EMD energy Hybrid model K-means clustering algorithm Monte Carlo method normal distribution Physical simulation prediction Transfer learning weather Deep learning K-means clustering algorithm Hybrid model Physical simulation Transfer learning EMD
ISSN:	0360-5442
On-line prístup:	Získať plný text
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