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A platform for research: civil engineering, architecture and urbanism
Very short-term chiller energy consumption prediction based on simplified heterogeneous graph convolutional network
https://orcid.org/0000-0001-7569-4084
https://orcid.org/0009-0000-0835-5568
https://orcid.org/0000-0003-4008-0773
Very short-term chiller energy consumption prediction based on simplified heterogeneous graph convolutional network
https://orcid.org/0000-0001-7569-4084
https://orcid.org/0009-0000-0835-5568
https://orcid.org/0000-0003-4008-0773
Very short-term chiller energy consumption prediction based on simplified heterogeneous graph convolutional network
https://orcid.org/0000-0001-7569-4084
https://orcid.org/0009-0000-0835-5568
https://orcid.org/0000-0003-4008-0773
Very short-term chiller energy consumption prediction based on simplified heterogeneous graph convolutional network
Energy and Buildings
Zhou, Kate Qi (author) / Adeepa Fernando, K.N. (author) / Dai, Xilei (author) / Liu, Jiuwei (author) / Li, Wen-Tai (author) / Lee, Christopher H.T. (author) / Cheong, Taesu (author) / Yuen, Chau (author)
Energy and Buildings ; 329 ; 115249
2025-02-01
Article (Journal)
Electronic Resource
English
| American Institute of Physics | 2022
Simplified energy prediction method accounting for part-load performance of chiller
| British Library Online Contents | 2007