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摘要:
Thermal comfort is the expression of people’s satisfaction with the indoor temperature and is related to people’s working efficiency and health. In this way, it is necessary to construct a suitable environment for the user. However, even if adaptive thermal comfort has been developing rapidly for the past decades, most of the models are still developed based on simple statistical analysis such as regression models, which may not capture the complex relations between thermal comfort and the indoor thermal environment as well as differences between individual characteristics. Hence, in order to improve the accuracy of the adaptive thermal comfort model, this paper proposes a decision-tree-based thermal comfort model developed with the subset of the RP884 dataset. Then, a comfort-based HVAC controller was developed with the thermal sensation prediction results with the trained model above. As a result, the proposed controller indeed improves occupant’s thermal comfort model.
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篇名 Personalized Thermal Comfort Model with Decision Tree
来源期刊 智能控制与自动化(英文) 学科 工学
关键词 THERMAL COMFORT DECISION Trees HVAC
年,卷(期) 2019,(4) 所属期刊栏目
研究方向 页码范围 168-177
页数 10页 分类号 TG1
字数 语种
DOI
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研究主题发展历程
节点文献
THERMAL
COMFORT
DECISION
Trees
HVAC
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研究分支
研究去脉
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相关学者/机构
期刊影响力
智能控制与自动化(英文)
季刊
2153-0653
武汉市江夏区汤逊湖北路38号光谷总部空间
出版文献量(篇)
250
总下载数(次)
0
总被引数(次)
0
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