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A data-driven approach for window opening predictions in non-air-conditioned buildings

Author(s): (Department of Architecture and Built Environment, University of Nottingham Ningbo China, Ningbo, People’s Republic of China)
ORCID (Department of Architecture and Built Environment, University of Nottingham Ningbo China, Ningbo, People’s Republic of China)
(Department of Architecture and Built Environment, University of Nottingham Ningbo China, Ningbo, People’s Republic of China)
ORCID (Urban Energy Systems Laboratory, Swiss Federal Laboratories for Materials Science and Technology, Dübendorf, Switzerland)
ORCID (Department of Architecture and Built Environment, University of Nottingham Ningbo China, Ningbo, People’s Republic of China)
(School of Mechanical & Automotive Engineering, Qilu University of Technology, Jinan, People’s Republic of China)
Medium: journal article
Language(s): English
Published in: Intelligent Buildings International, , n. 3, v. 14
Page(s): 1-17
DOI: 10.1080/17508975.2021.1963651
Structurae cannot make the full text of this publication available at this time. The full text can be accessed through the publisher via the DOI: 10.1080/17508975.2021.1963651.
  • About this
    data sheet
  • Reference-ID
    10626921
  • Published on:
    05/09/2021
  • Last updated on:
    23/09/2022
 
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