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Leveraging machine learning techniques and in-situ measurements for precise predicting the energy performance of regenerative counter-flow indirect evaporative cooler in a semi-arid climate building

Author(s):
ORCID

Medium: journal article
Language(s): English
Published in: Journal of Building Engineering, , v. 95
Page(s): 110318
DOI: 10.1016/j.jobe.2024.110318
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: 10.1016/j.jobe.2024.110318.
  • About this
    data sheet
  • Reference-ID
    10817904
  • Published on:
    03/02/2025
  • Last updated on:
    03/02/2025
 
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