热舒适性
暖通空调
环境科学
空气温度
工作温度
航程(航空)
逻辑回归
线性回归
热的
气象学
能源消耗
气候带
计算机科学
统计
工程类
空调
地理
数学
机械工程
航空航天工程
电气工程
自然地理学
作者
Heng Du,Zhiwei Lian,Dayi Lai,Weiwei Liu,Lin Duanmu,Yongchao Zhai,Bin Cao,Yufeng Zhang,Xiang Zhou,Zhaojun Wang,Xiaojing Zhang
标识
DOI:10.1016/j.enbuild.2021.110920
摘要
Indoor thermal environment design parameters have a significant impact on human thermal comfort, health and building energy consumption. The methods of determining indoor thermal environment design parameters in China and around the world are mainly based on the PMV model. This method often results in certain errors deviations from the actual situation and has difficulty reflecting the differences in the thermal environmental requirements in different climate regions, seasons, building types, etc. This paper proposes a data-driven method based on Chinese Thermal Comfort Database and uses a logistic regression to obtain the indoor air temperature range that 80% of occupants find thermally acceptable under different conditions. The results indicate that the prediction of this model are in good agreement with the actual data and have as higher accuracy in predicting the percentage of thermal acceptability than a linear regression method. This model shows that different regions, seasons, and building types have different acceptable temperature ranges and that the acceptable air temperature ranges are on average 2.0 °C wider than the ISO 7730 and 0.7 °C wider than the GB50736-2012. This method is conducive to the determination of air temperature thresholds and better reflects people's equirements for thermal environment under different conditions.
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