The DOI matches its Crossref record; 57 of the 57 references it cites were found in a registry or an index.
Personal comfort models: Predicting individuals' thermal preference using occupant heating and cooling behavior and machine learning
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Citations
Cites
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A review on buildings energy consumption information
Pérez-Lombard, L., Ortiz, J., & Pout, C. (2008) · Energy and Buildings · doi:10.1016/j.enbuild.2007.03.007 · Cited by 6,649
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Data Mining for Imbalanced Datasets: An Overview
Chawla, N. V. (2009) · Data Mining and Knowledge Discovery Handbook · doi:10.1007/978-0-387-09823-4_45 · Cited by 1,082
An experimental comparison of performance measures for classification
Ferri, C., Hernández-Orallo, J., & Modroiu, R. (2009) · Pattern Recognition Letters · doi:10.1016/j.patrec.2008.08.010 · Cited by 889
Cited by
Individual difference in thermal comfort: A literature review
Wang, Z., de Dear, R., Luo, M., Lin, B., He, Y., Ghahramani, A., & Zhu, Y. (2018) · Building and Environment · doi:10.1016/j.buildenv.2018.04.040 · Cited by 675
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
Drivers of diversity in human thermal perception – A review for holistic comfort models
Schweiker, M., Huebner, G. M., Kingma, B. R. M., Kramer, R., & Pallubinsky, H. (2018) · Temperature · doi:10.1080/23328940.2018.1534490 · Cited by 231
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
Metadata
- Authors
- Kim, J., Zhou, Y., Schiavon, S., Raftery, P., & Brager, G.
- Venue
- Building and Environment
- Publisher
- Elsevier BV
- Published
- 2018-02
- Volume
- 129
- Pages
- 96-106
- ISSN
- 0360-1323 (ISSN-L)
- OpenAlex
- W2774931648
- Cited by
- 478
- References
- 57
- FWCI
- 34.15
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Personal comfort models: Predicting individuals' thermal preference using occupant heating and cooling behavior and machine learning. https://app.cochat.ai/papers/10.1016/j.buildenv.2017.12.011
- The paper
- Kim, J., Zhou, Y., Schiavon, S., Raftery, P., & Brager, G. (2018). Personal comfort models: Predicting individuals' thermal preference using occupant heating and cooling behavior and machine learning. Building and Environment. https://doi.org/10.1016/j.buildenv.2017.12.011
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.
