The DOI matches its Crossref record; 98 of the 98 references it cites were found in a registry or an index.
Review of building energy modeling for control and operation
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Citations
Cites
System Identification: Theory for the User
Lennart Ljung, A. (1987) · Cited by 17,690
System identification—Theory for the user
Sinha, N. K. (1989) · Automatica · doi:10.1016/0005-1098(89)90019-8 · Cited by 9,184
The interrelationship and characteristic distribution of direct, diffuse and total solar radiation
Liu, B. Y. H., & Jordan, R. C. (1960) · Solar Energy · doi:10.1016/0038-092x(60)90062-1 · Cited by 2,489
Modeling daylight availability and irradiance components from direct and global irradiance
Perez, R., Ineichen, P., Seals, R., Michalsky, J., & Stewart, R. (1990) · Solar Energy · doi:10.1016/0038-092x(90)90055-h · Cited by 1,999
Contrasting the capabilities of building energy performance simulation programs
Crawley, D. B., Hand, J. W., Kummert, M., & Griffith, B. T. (2008) · Building and Environment · doi:10.1016/j.buildenv.2006.10.027 · Cited by 1,858
1987 american control conference
(1987) · IEEE Control Systems Magazine · doi:10.1109/mcs.1987.1105260 · Cited by 1,402
Photovoltaic array performance model.
Kratochvil, J., Boyson, W., & King, D. (2004) · doi:10.2172/919131 · Cited by 1,340
Use of model predictive control and weather forecasts for energy efficient building climate control
Oldewurtel, F., Parisio, A., Jones, C. N., Gyalistras, D., Gwerder, M., Stauch, V., Lehmann, B., & Morari, M. (2012) · Energy and Buildings · doi:10.1016/j.enbuild.2011.09.022 · Cited by 1,222
Katipamula, S., & Brambley, M. R. (2005) · HVAC&R Research · doi:10.1080/10789669.2005.10391123 · Cited by 936
Dynamic lithium-ion battery model for system simulation
Gao, L., Liu, S., & Dougal, R. A. (2002) · IEEE Transactions on Components and Packaging Technologies · doi:10.1109/tcapt.2002.803653 · Cited by 794
Cited by
A review of data-driven building energy consumption prediction studies
Amasyali, K., & El-Gohary, N. M. (2018) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2017.04.095 · Cited by 1,874
Ahmad, M. W., Mourshed, M., & Rezgui, Y. (2017) · Energy and Buildings · doi:10.1016/j.enbuild.2017.04.038 · Cited by 1,013
Reinforcement learning for demand response: A review of algorithms and modeling techniques
Vázquez-Canteli, J. R., & Nagy, Z. (2019) · Applied Energy · doi:10.1016/j.apenergy.2018.11.002 · Cited by 883
Wang, Z., & Srinivasan, R. S. (2017) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2016.10.079 · Cited by 678
Serale, G., Fiorentini, M., Capozzoli, A., Bernardini, D., & Bemporad, A. (2018) · Energies · doi:10.3390/en11030631 · Cited by 637
Metadata
- Authors
- Li, X., & Wen, J.
- Venue
- Renewable and Sustainable Energy Reviews
- Publisher
- Elsevier BV
- Published
- 2014-09
- Volume
- 37
- Pages
- 517-537
- ISSN
- 1364-0321 (ISSN-L)
- OpenAlex
- W1965345917
- Cited by
- 629
- References
- 98
- FWCI
- 51.96
- Type
- journal article
- Language
- en
- Open access
- closed
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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- CoChat. (2026). Citation check: Review of building energy modeling for control and operation. https://app.cochat.ai/papers/10.1016/j.rser.2014.05.056
- The paper
- Li, X., & Wen, J. (2014). Review of building energy modeling for control and operation. Renewable and Sustainable Energy Reviews. https://doi.org/10.1016/j.rser.2014.05.056
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.
