Open Access
E3S Web of Conf.
Volume 396, 2023
The 11th International Conference on Indoor Air Quality, Ventilation & Energy Conservation in Buildings (IAQVEC2023)
Article Number 01064
Number of page(s) 4
Section Indoor Environmental Quality (IEQ), Human Health, Comfort and Productivity
Published online 16 June 2023
  1. IEA, World Energy Outlook 2022, IEA, Paris, License: CC BY 4.0 (report); CC BY NC SA 4.0 (Annex A) (2022) [Google Scholar]
  2. J. Guenther, S. Oliver, Feature Selection for Thermal Comfort Modeling based on Constrained LASSO Regression, IFAC-PapersOnLine, Volume 52, Issue 15, 2019, Pages 400-405 (2019) [CrossRef] [Google Scholar]
  3. L. Lan, P. Wargocki, & D. P. Wyon, Z, Lian. Effects of thermal discomfort in an office on perceived air quality, SBS symptoms, physiological responses, and human performance. Indoor air. 21. 376-90. (2011) [CrossRef] [PubMed] [Google Scholar]
  4. D. P. Wyon, I. B. Andersen, G.R. Lundqvist, The effects of moderate heat stress on mental performance. Scandinavian J. Work, Environment & Health, 5, 352-361. (1979) [Google Scholar]
  5. C. Ana, N. Sandro, S. Petar, P. Toni, A. Aleksandar, C. Velimir, Investigation of personal thermal comfort in office building by implementation of smart bracelet: A case study, Energy, Volume 260, 2022, 124973. (2022) [CrossRef] [Google Scholar]
  6. ASHRAE, ANSI/ASHRAE Standard 55-2017 Thermal Environmental Conditions for Human Occupancy, In. Atlanta: ASHRAE. (2017) [Google Scholar]
  7. P.O. Fänger, Fundamentals of Thermal Comfort, Advances In Solar Energy Technology. W. H. Bloss and F. Pfisterer, Oxford, 3056-3061. (1988) [CrossRef] [Google Scholar]
  8. X. Zhou, L. Xu, J. Zhang, B. Niu, M. Luo, G. Zhou, X. Zhang, Data-driven thermal comfort model via support vector machine algorithms: Insights from ASHRAE RP-884 database. Energy and Buildings, 211, 109795. (2020) [CrossRef] [Google Scholar]
  9. D. Li, C. C. Menassa, V. R. Kamat, Personalized human comfort in indoor building environments under diverse conditioning modes. Building and Environment, 126, 304-317. (2017) [CrossRef] [Google Scholar]
  10. F. Mousa, H. Hamdy, Real-Time Intelligent Thermal Comfort Prediction Model. International Journal of Advanced Computer Science and Applications, 12. (2021) [Google Scholar]
  11. J. Guenther, S. Oliver, Feature Selection for Thermal Comfort Modeling based on Constrained LASSO Regression. IFAC-PapersOnLine, Volume 52, Issue 15, 2019, Pages 400-405. ISSN 2405-8963. (2019) [CrossRef] [Google Scholar]
  12. G. Puyue, C. Yuanzhi, Z. Zihan, Z. Cheng, C. Bing, S. Stephen, Investigating spatial impact on indoor personal thermal comfort. Journal of Building Engineering, Volume 45, 2022,103536. (2022) [CrossRef] [Google Scholar]
  13. S. M. Taib, S. A. Zaki, H. B. Rijal, A. A. Razak, A. Hagishima, W. Khalid, M. S. M. Ali, Associating thermal comfort and preference in Malaysian universities’ air-conditioned office rooms under various set-point temperatures. Journal of Building Engineering 54, 104575. (2022) [CrossRef] [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.