Evaluation of machine learning methods for thermal sensation and comfort predictions in microenvironments created by personal conditioning devices-Reference-Cited by-同舟云学术

Evaluation of machine learning methods for thermal sensation and comfort predictions in microenvironments created by personal conditioning devices

Published:2022-11-09 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 9th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation
language:
Short-container-title:

Author:

Wang Lingzhe¹,Dalgo Daniel A.²,Mattise Nicholas¹,Zhu Shengwei¹,Srebric Jelena¹

Affiliation:

1. University of Maryland, College Park

2. Montgomery College

Funder

MEI Seed Grant, University of Maryland, College Park

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3563357.3567758

Reference4 articles.

1. ASHRAE. 2020. Standard 55 - Thermal Environmental Conditions for Human Occupancy. (2020). ASHRAE. 2020. Standard 55 - Thermal Environmental Conditions for Human Occupancy. (2020).

2. Energy savings and thermal comfort evaluation of a novel personal conditioning device

3. Observations of upper-extremity skin temperature and corresponding overall-body thermal sensations and comfort

4. Lingzhe Wang , Daniel A. Dalgo , Nicholas Mattise , Shengwei Zhu , and Jelena Srebric . 2022. Physiological Responses and Data-Driven Thermal Comfort Models with Personal Conditioning Devices (PCD). Manuscript submitted for publication ( 2022 ). Lingzhe Wang, Daniel A. Dalgo, Nicholas Mattise, Shengwei Zhu, and Jelena Srebric. 2022. Physiological Responses and Data-Driven Thermal Comfort Models with Personal Conditioning Devices (PCD). Manuscript submitted for publication (2022).

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A wearable micro air cleaner for occupant-oriented indoor environmental controls;Building and Environment;2023-09

2. A Wearable Micro Air Cleaner for Occupant-Oriented Indoor Environmental Controls;2023