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Developing machine-learning meta-models for high-rise residential district cooling in hot and humid climate

Author(s): (Centre for Zero Energy Building Studies, Department of Building, Civil and Environmental Engineering, Concordia University, Montreal, Canada)
(Centre for Zero Energy Building Studies, Department of Building, Civil and Environmental Engineering, Concordia University, Montreal, Canada)
(Mechanical Engineering Program, Texas A&M University at Qatar, Doha, Qatar)
(Mechanical Engineering Program, Texas A&M University at Qatar, Doha, Qatar)
(Centre for Zero Energy Building Studies, Department of Building, Civil and Environmental Engineering, Concordia University, Montreal, Canada)
Medium: journal article
Language(s): English
Published in: Journal of Building Performance Simulation, , n. 4, v. 15
Page(s): 1-21
DOI: 10.1080/19401493.2021.2001573
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: 10.1080/19401493.2021.2001573.
  • About this
    data sheet
  • Reference-ID
    10648606
  • Published on:
    07/01/2022
  • Last updated on:
    20/06/2022
 
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