摘要
Recent studies on thermal comfort often require feedback from occupants or additional devices installed. This often limits the scalability of these approaches. In this paper, we for the first time study thermal comfort prediction of an occupant by training a model from the data of not only the targeted occupant but also others, guided by domain knowledge. We demonstrate, using ASHRAE data, that this approach has potential, and is worth exploring.
| 源语言 | 英语 |
|---|---|
| 主期刊名 | e-Energy 2018 - Proceedings of the 9th ACM International Conference on Future Energy Systems |
| 出版商 | Association for Computing Machinery, Inc |
| 页 | 271-276 |
| 页数 | 6 |
| ISBN（电子版） | 9781450357678 |
| DOI | |
| 出版状态 | 已出版 - 12 6月 2018 |
| 活动 | 9th ACM International Conference on Future Energy Systems, e-Energy 2018 - Karlsruhe, 德国 期限: 12 6月 2018 → 15 6月 2018 |
出版系列
| 姓名 | e-Energy 2018 - Proceedings of the 9th ACM International Conference on Future Energy Systems |
|---|
会议
| 会议 | 9th ACM International Conference on Future Energy Systems, e-Energy 2018 |
|---|---|
| 国家/地区 | 德国 |
| 市 | Karlsruhe |
| 时期 | 12/06/18 → 15/06/18 |
指纹
探究 'A domain-Assisted data driven model for thermal comfort prediction in buildings' 的科研主题。它们共同构成独一无二的指纹。引用此
Yang, L., Zheng, Z., Sun, J., Wang, D., & Li, X. (2018). A domain-Assisted data driven model for thermal comfort prediction in buildings. 在 e-Energy 2018 - Proceedings of the 9th ACM International Conference on Future Energy Systems (页码 271-276). (e-Energy 2018 - Proceedings of the 9th ACM International Conference on Future Energy Systems). Association for Computing Machinery, Inc. https://doi.org/10.1145/3208903.3208914