PreprintArticleVersion 1This version is not peer-reviewed
Human-Centred Perception as a Mediator of Environmental Decision-Making: A Study on the Suitability Parameters of Public Underground Spaces – a Case Study of Wujiaochang, Shanghai
Version 1
: Received: 2 October 2024 / Approved: 3 October 2024 / Online: 3 October 2024 (10:54:47 CEST)
How to cite:
Tianning, Y.; Sun, L.; Geng, L.; Xu, Y.; Hu, K.; Chen, X.; Liao, P.; Wang, J. Human-Centred Perception as a Mediator of Environmental Decision-Making: A Study on the Suitability Parameters of Public Underground Spaces – a Case Study of Wujiaochang, Shanghai. Preprints2024, 2024100223. https://doi.org/10.20944/preprints202410.0223.v1
Tianning, Y.; Sun, L.; Geng, L.; Xu, Y.; Hu, K.; Chen, X.; Liao, P.; Wang, J. Human-Centred Perception as a Mediator of Environmental Decision-Making: A Study on the Suitability Parameters of Public Underground Spaces – a Case Study of Wujiaochang, Shanghai. Preprints 2024, 2024100223. https://doi.org/10.20944/preprints202410.0223.v1
Tianning, Y.; Sun, L.; Geng, L.; Xu, Y.; Hu, K.; Chen, X.; Liao, P.; Wang, J. Human-Centred Perception as a Mediator of Environmental Decision-Making: A Study on the Suitability Parameters of Public Underground Spaces – a Case Study of Wujiaochang, Shanghai. Preprints2024, 2024100223. https://doi.org/10.20944/preprints202410.0223.v1
APA Style
Tianning, Y., Sun, L., Geng, L., Xu, Y., Hu, K., Chen, X., Liao, P., & Wang, J. (2024). Human-Centred Perception as a Mediator of Environmental Decision-Making: A Study on the Suitability Parameters of Public Underground Spaces – a Case Study of Wujiaochang, Shanghai. Preprints. https://doi.org/10.20944/preprints202410.0223.v1
Chicago/Turabian Style
Tianning, Y., Pan Liao and Jin Wang. 2024 "Human-Centred Perception as a Mediator of Environmental Decision-Making: A Study on the Suitability Parameters of Public Underground Spaces – a Case Study of Wujiaochang, Shanghai" Preprints. https://doi.org/10.20944/preprints202410.0223.v1
Abstract
With the acceleration of urbanisation and the increase in underground space use, how to provide a comfortable and healthy environment in underground space has become an important research topic. This study constructed an environmental decision-making model for underground space by integrating human perception evaluation and physical environment factors. The study analysed the influence of physical environment parameters on users' perceived experience through field data collection and questionnaire surveys. The data were in-depth analysed using single-indicator fitted regression analysis and XGBoost machine learning model. The results reveal the significant influence of physical parameters such as temperature, humidity, illuminance and wind speed on the comfort of users of underground spaces and determine the range of appropriateness of these physical environment parameters. The results provide a reliable theoretical basis for optimising the design and management of underground spaces and help to enhance the environmental quality and user experience of underground spaces.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
