A measurement-based framework integrating machine learning and morphological dynamics for outdoor thermal regulation
This study presents a comprehensive investigation into the interplay between machine learning (ML) models, morphological features, and outdoor thermal comfort (OTC) across three key indices: Universal Thermal Climate Index (UTCI), Physiological Equivalent Temperature (PET), and Predicted Mean Vote (...
Elmentve itt :
| Szerzők: |
Alinasab Niloufar Mohammadzadeh Negar Karimi Alireza Mohammadzadeh Rahmat Gál Tamás Mátyás |
|---|---|
| Dokumentumtípus: | Cikk |
| Megjelent: |
2025
|
| Sorozat: | INTERNATIONAL JOURNAL OF BIOMETEOROLOGY
69 No. 7 |
| Tárgyszavak: | |
| doi: | 10.1007/s00484-025-02921-8 |
| mtmt: | 36099916 |
| Online Access: | http://publicatio.bibl.u-szeged.hu/39009 |
Hasonló tételek
-
Integrating Machine Learning and Genetic Algorithms to Optimize Building Energy and Thermal Efficiency Under Historical and Future Climate Scenarios
Szerző: Alireza Karimi, et al.
Megjelent: (2024) -
Investigating Outdoor Thermal Comfort in Various Street Patterns (Case Study A Neighborhood in the Historical Context of Tabriz) /
Szerző: Saber Sabouri, et al.
Megjelent: (2021) -
Effects of street design on outdoor thermal comfort
Szerző: Fazia Ali-Toudert, et al.
Megjelent: (2006) -
Assessments of the outdoor thermal conditions in Szeged, Hungary thermal sensation ranges for local residents /
Szerző: Kántor Noémi, et al.
Megjelent: (2011) -
Protein classification in a machine learning framework
Szerző: Kertész-Farkas Attila
Megjelent: (2009)