The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Spatial distribution of urban building energy consumption by end use
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Citations
Cites
Modeling of end-use energy consumption in the residential sector: A review of modeling techniques
Swan, L. G., & Ugursal, V. I. (2009) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2008.09.033 · Cited by 1,934
Tso, G. K. F., & Yau, K. K. W. (2007) · Energy · doi:10.1016/j.energy.2006.11.010 · Cited by 933
Residential Energy Consumption Survey (2016)
Liao, H. (2019) · Harvard Dataverse · doi:10.7910/dvn/agbpxs · Cited by 415
Heiple, S., & Sailor, D. J. (2008) · Energy and Buildings · doi:10.1016/j.enbuild.2008.01.005 · Cited by 323
Modelling the electricity consumption of cities: effect of urban density
Larivière, I., & Lafrance, G. (1999) · Energy Economics · doi:10.1016/s0140-9883(98)00007-3 · Cited by 202
Sustainable cities – modelling urban energy supply and demand
Brownsword, R. A., Fleming, P., Powell, J. C., & Pearsall, N. M. (2004) · Applied Energy · doi:10.1016/j.apenergy.2004.10.005 · Cited by 69
Estimation of energy intensity by end-use for commercial buildings
Turiel, I., Craig, P., Levine, M., McMahon, J., McCollister, G. M., Hesterberg, B., & Robinson, M. C. (1987) · Energy · doi:10.1016/0360-5442(87)90003-x · Cited by 17
Cited by
Urban building energy modeling – A review of a nascent field
Reinhart, C. F., & Cerezo Davila, C. (2016) · Building and Environment · doi:10.1016/j.buildenv.2015.12.001 · Cited by 1,081
Hoffman, J. S., Shandas, V., & Pendleton, N. (2020) · Climate · doi:10.3390/cli8010012 · Cited by 842
A review of data-driven approaches for prediction and classification of building energy consumption
Wei, Y., Zhang, X., Shi, Y., Xia, L., Pan, S., Wu, J., Han, M., & Zhao, X. (2018) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2017.09.108 · Cited by 803
Jain, R. K., Smith, K. M., Culligan, P. J., & Taylor, J. E. (2014) · Applied Energy · doi:10.1016/j.apenergy.2014.02.057 · Cited by 600
Machine learning approaches for estimating commercial building energy consumption
Robinson, C., Dilkina, B., Hubbs, J., Zhang, W., Guhathakurta, S., Brown, M. A., & Pendyala, R. M. (2017) · Applied Energy · doi:10.1016/j.apenergy.2017.09.060 · Cited by 482
Metadata
- Authors
- Howard, B., Parshall, L., Thompson, J., Hammer, S., Dickinson, J., & Modi, V.
- Venue
- Energy and Buildings
- Publisher
- Elsevier BV
- Published
- 2012-02
- Volume
- 45
- Pages
- 141-151
- ISSN
- 0378-7788 (ISSN-L)
- OpenAlex
- W1966671713
- Cited by
- 428
- References
- 7
- FWCI
- 36.70
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Spatial distribution of urban building energy consumption by end use. https://app.cochat.ai/papers/10.1016/j.enbuild.2011.10.061
- The paper
- Howard, B., Parshall, L., Thompson, J., Hammer, S., Dickinson, J., & Modi, V. (2012). Spatial distribution of urban building energy consumption by end use. Energy and Buildings. https://doi.org/10.1016/j.enbuild.2011.10.061
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.
