The DOI matches its Crossref record; 66 of the 66 references it cites were found in a registry or an index.
Personal comfort models – A new paradigm in thermal comfort for occupant-centric environmental control
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Cites
Data Mining: Practical Machine Learning Tools and Techniques
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Nasrabadi, N. M. (2007) · Journal of Electronic Imaging · doi:10.1117/1.2819119 · Cited by 22,066
The meaning and use of the area under a receiver operating characteristic (ROC) curve.
Hanley, J. A., & McNeil, B. J. (1982) · Radiology · doi:10.1148/radiology.143.1.7063747 · Cited by 21,856
The magical number seven, plus or minus two: Some limits on our capacity for processing information.
Miller, G. A. (1956) · Psychological Review · doi:10.1037/h0043158 · Cited by 17,812
The magical number seven, plus or minus two: Some limits on our capacity for processing information.
Miller, G. A. (1994) · Psychological Review · doi:10.1037/0033-295x.101.2.343 · Cited by 17,161
Pattern Recognition and Machine Learning
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Thermal comfort: Analysis and applications in environmental engineering
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Adaptive thermal comfort and sustainable thermal standards for buildings
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Kernel methods in machine learning
Hofmann, T., Schölkopf, B., & Smola, A. J. (2008) · The Annals of Statistics · doi:10.1214/009053607000000677 · Cited by 1,651
Cited by
Ten questions concerning well-being in the built environment
Altomonte, S., Allen, J., Bluyssen, P. M., Brager, G., Heschong, L., Loder, A., Schiavon, S., Veitch, J. A., Wang, L., & Wargocki, P. (2020) · Building and Environment · doi:10.1016/j.buildenv.2020.106949 · Cited by 303
Self-citationPark, J. Y., Dougherty, T., Fritz, H., & Nagy, Z. (2019) · Building and Environment · doi:10.1016/j.buildenv.2018.10.028 · Cited by 238
Revisiting individual and group differences in thermal comfort based on ASHRAE database
Wang, Z., Zhang, H., He, Y., Luo, M., Li, Z., Hong, T., & Lin, B. (2020) · Energy and Buildings · doi:10.1016/j.enbuild.2020.110017 · Cited by 123
Machine Learning for Smart and Energy-Efficient Buildings
Das, H. P., Lin, Y.-W., Agwan, U., Spangher, L., Devonport, A., Yang, Y., Drgoňa, J., Chong, A., Schiavon, S., & Spanos, C. J. (2024) · Environmental Data Science · doi:10.1017/eds.2023.43 · Cited by 78
Self-citationAli, B. M., & Akkaş, M. (2023) · Applied Sciences · doi:10.3390/app14010195 · Cited by 51
Metadata
- Authors
- Kim, J., Schiavon, S., & Brager, G.
- Venue
- Building and Environment
- Publisher
- Elsevier BV
- Published
- 2018-03
- Volume
- 132
- Pages
- 114-124
- ISSN
- 0360-1323 (ISSN-L)
- OpenAlex
- W2783850388
- Cited by
- 522
- References
- 66
- FWCI
- 34.43
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Kim, J., Schiavon, S., & Brager, G. (2018). Personal comfort models – A new paradigm in thermal comfort for occupant-centric environmental control. Building and Environment. https://doi.org/10.1016/j.buildenv.2018.01.023
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
