Informing building retrofits at low computational costs: a multi-objective optimisation using machine learning surrogates of building performance simulation models
| Autor(en): |
Elin Markarian
(Department of Civil and Environmental Engineering, Carleton University, Ottawa, Canada)
Seif Qiblawi (Department of Civil and Environmental Engineering, Carleton University, Ottawa, Canada) Shivram Krishnan (Department of Civil Engineering, IIT Bombay, Powai, Mumbai, India) Anagha Divakaran (Department of Civil Engineering, IIT Bombay, Powai, Mumbai, India) Omprakash Ramalingam Rethnam (Department of Civil Engineering, IIT Bombay, Powai, Mumbai, India) Albert Thomas (Department of Civil Engineering, IIT Bombay, Powai, Mumbai, India) Elie Azar 
(Department of Civil and Environmental Engineering, Carleton University, Ottawa, Canada)
|
|---|---|
| Medium: | Fachartikel |
| Sprache(n): | Englisch |
| Veröffentlicht in: | Journal of Building Performance Simulation |
| Seite(n): | 1-17 |
| DOI: | 10.1080/19401493.2024.2384487 |
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Datenseite - Reference-ID
10797276 - Veröffentlicht am:
01.09.2024 - Geändert am:
01.09.2024
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