Transformer based day-ahead cooling load forecasting of hub airport air-conditioning systems with thermal energy storage

Yu, D., Liu, T., Wang, K. et al. (5 more authors) (2024) Transformer based day-ahead cooling load forecasting of hub airport air-conditioning systems with thermal energy storage. Energy and Buildings, 308. 114008. ISSN 0378-7788

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Item Type: Article
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© 2024 Elsevier B.V. This is an author produced version of an article published in Energy and Buildings. Uploaded in accordance with the publisher's self-archiving policy. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/.

Keywords: Day-ahead cooling load prediction, Weighted-DTW-k-means, Interpretable deep learning model, Temporal fusion transformer (TFT), Performance evaluation
Dates:
  • Published: 1 April 2024
  • Published (online): 21 February 2024
  • Accepted: 14 February 2024
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Institute of Communication & Power Networks (Leeds)
Depositing User: Symplectic Publications
Date Deposited: 02 Jul 2024 14:54
Last Modified: 21 Feb 2025 01:13
Status: Published
Publisher: Elsevier
Identification Number: 10.1016/j.enbuild.2024.114008
Sustainable Development Goals:
  • Sustainable Development Goals: Goal 7: Affordable and Clean Energy
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