0
  • DE
  • EN
  • FR
  • International Database and Gallery of Structures

Advertisement

Limitations and issues of conventional artificial neural network-based surrogate models for building energy retrofit

Author(s): (Department of Architecture and Architectural Engineering, College of Engineering, Seoul National University, Seoul, South Korea)
(Department of Architecture and Architectural Engineering, Institute of Construction and Environmental Engineering, Institute of Engineering Research, College of Engineering, Seoul National University, Seoul, South Korea)
Medium: journal article
Language(s): English
Published in: Journal of Building Performance Simulation, , n. 3, v. 17
Page(s): 1-10
DOI: 10.1080/19401493.2023.2282078
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: 10.1080/19401493.2023.2282078.
  • About this
    data sheet
  • Reference-ID
    10755609
  • Published on:
    14/01/2024
  • Last updated on:
    24/04/2024
 
Structurae cooperates with
International Association for Bridge and Structural Engineering (IABSE)
e-mosty Magazine
e-BrIM Magazine