A novel machine learning-based framework for mapping outdoor thermal comfort-Reference-Cited by-同舟云学术

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A novel machine learning-based framework for mapping outdoor thermal comfort

Published:2022-12-05 Issue:1 Volume:17 Page:53-72
ISSN:1751-2549
Container-title:Advances in Building Energy Research
language:en
Short-container-title:Advances in Building Energy Research

Author:

Shahrestani Seyed Shayan¹,Zomorodian Zahra Sadat¹^ORCID,Karami Maryam²,Mostafavi Fatemeh³

Affiliation:

1. Department of Construction, Shahid Beheshti University, Tehran, Iran

2. Department of Mechanical Engineering, Kharazmi University, Tehran, Iran

3. Faculty of Architecture and the Built Environment, Delft University of Technology, Delft, the Netherlands

Publisher

Informa UK Limited

Subject

Building and Construction

Link

https://www.tandfonline.com/doi/pdf/10.1080/17512549.2022.2152865

Reference40 articles.

1. Outdoor thermal comfort: Analyzing the impact of urban configurations on the thermal performance of street canyons in the humid subtropical climate of Sydney

2. A comprehensive review of outdoor thermal comfort in urban areas: Effective parameters and approaches

3. Investigating the thermal performance of green wall: Experimental analysis, deep learning model, and simulation studies in a humid climate

4. Validation of UWG and ENVI-Met Models in an Abu Dhabi District, Based on Site Measurements

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3. Assessment and prediction of pedestrian thermal comfort through machine learning modelling in tropical urban climate of Nagpur City;Theoretical and Applied Climatology;2024-04-13

4. Supervised Machine Learning Technology Applications in Outdoor Thermal Comfort: A Systematic Review;2024

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