التفاصيل البيبلوغرافية
| العنوان: |
Exploring Optimisation Pathways for Underground Space Quality Under the Synergy of Multidimensional Perception and Environmental Parameters. |
| المؤلفون: |
Yao, Tianning, Sun, Liang, Geng, Lin, Xu, Yao, Xu, Ziqi, Hu, Kuntao, Chen, Xing, Liao, Pan, Wang, Jin |
| المصدر: |
Buildings (2075-5309); Jan2025, Vol. 15 Issue 2, p204, 27p |
| مصطلحات موضوعية: |
UNDERGROUND areas, GEOGRAPHICAL perception, PUBLIC spaces, SPACE environment, WIND speed |
| مستخلص: |
With the acceleration of urbanisation and the increased utilisation of underground space, providing a comfortable and healthy environment in public underground areas has emerged as a significant research topic. This study constructs a comprehensive decision-making framework for underground space environments by integrating human perception evaluations with physical environmental parameters. Using Shanghai Wujiaochang as a case study, field data collection and questionnaire surveys were conducted to evaluate key factors such as temperature (22.63 °C–26.39 °C), wind speed (0.26 m/s–0.67 m/s), and sound levels (59.68 dB–61.21 dB) for commercial-oriented spaces, and 63.15 dB–75.45 dB for transport-oriented spaces) to users' perceived experiences. The appropriate ranges for key parameters were identified through single-indicator fitted regression analysis and the XGBoost machine-learning model, revealing the relationship between environmental parameters and human perception. The results indicated significant differences in user needs across various functional spaces, with commercial-oriented areas emphasising environmental attractiveness and comfort, while transport-oriented spaces prioritised access efficiency and safety. This study provided quantitative design benchmarks for underground spaces' dynamic regulation and sustainable management, proposing a precise and adaptive environmental decision-making framework that combines physical parameters with user-perception feedback. [ABSTRACT FROM AUTHOR] |
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| قاعدة البيانات: |
Complementary Index |
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