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An indoor airflow distribution predictor using machine learning for a real-time healthy building monitoring system in the tropics

Auteur(s): ORCID (Department of Nuclear Engineering and Engineering Physics, Universitas Gadjah Mada, Yogyakarta, Indonesia)
ORCID (Department of Nuclear Engineering and Engineering Physics, Universitas Gadjah Mada, Yogyakarta, Indonesia)
ORCID (Institute for Environmental Design and Engineering, University College London, London, UK)
ORCID (Department of Nuclear Engineering and Engineering Physics, Universitas Gadjah Mada, Yogyakarta, Indonesia)
ORCID (Department of Nuclear Engineering and Engineering Physics, Universitas Gadjah Mada, Yogyakarta, Indonesia)
ORCID (Department of Nuclear Engineering and Engineering Physics, Universitas Gadjah Mada, Yogyakarta, Indonesia)
Médium: article de revue
Langue(s): anglais
Publié dans: Building Services Engineering Research and Technology, , n. 3, v. 45
Page(s): 293-315
DOI: 10.1177/01436244241231354
Structurae ne peut pas vous offrir cette publication en texte intégral pour l'instant. Le texte intégral est accessible chez l'éditeur. DOI: 10.1177/01436244241231354.
  • Informations
    sur cette fiche
  • Reference-ID
    10760901
  • Publié(e) le:
    23.03.2024
  • Modifié(e) le:
    20.09.2024
 
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