Occupancy schedules learning process through a data mining framework
Open accessIntegrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Occupancy detection represents an opportunity for ML algorithms, ranging from decision trees to deep neural networks using various inputs.
“Moreover, occupancy detection itself represents an opportunity for ML algorithms, ranging from decision trees [193,882] to deep neural networks [896] that take input from occupancy sensors [193], WiFi signals [896,897], or appliance power consumption data [882].”
From Tackling climate change with machine learning (2023) · cites this paper as [193]
Cites
Classification and Regression Trees.
Gordon, A. D., Breiman, L., Friedman, J. H., Olshen, R. A., & Stone, C. J. (1984) · Biometrics · doi:10.2307/2530946 · Cited by 23,834 · see citing works
Classification and Regression Trees.
Ryzin, J. V., Breiman, L., Friedman, J. H., Olshen, R. A., & Stone, C. J. (1986) · Journal of the American Statistical Association · doi:10.2307/2288003 · Cited by 21,028 · see citing works
Davies, D. L., & Bouldin, D. W. (1979) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.1979.4766909 · Cited by 9,145 · see citing works
Advances in knowledge discovery and data mining
(1996) · Computers & Mathematics with Applications · doi:10.1016/s0898-1221(96)90007-3 · Cited by 2,996 · see citing works
Quinlan, J. R. (1987) · International Journal of Man-Machine Studies · doi:10.1016/s0020-7373(87)80053-6 · Cited by 2,553 · see citing works
Hand, D. J., Mannila, H., & Smyth, P. (2001) · Cited by 2,382 · see citing works
Fast discovery of association rules
Agrawal, R., Mannila, H., Srikant, R., Toivonen, H. T. T., & Verkamo, A. I. (1996) · Knowledge Discovery and Data Mining · Cited by 2,376 · see citing works
From data mining to knowledge discovery: an overview
Fayyad, U. M., Piatetsky-Shapiro, G., & Smyth, P. (1996) · Knowledge Discovery and Data Mining · Cited by 2,319 · see citing works
Smith, A. E. (2002) · Artificial Intelligence in Medicine · doi:10.1016/s0933-3657(02)00058-1 · Cited by 1,711 · see citing works
Frequent pattern mining: current status and future directions
Han, J., Cheng, H., Xin, D., & Yan, X. (2007) · Data Mining and Knowledge Discovery · doi:10.1007/s10618-006-0059-1 · Cited by 1,383 · see citing works
A generalised stochastic model for the simulation of occupant presence
Page, J., Robinson, D., Morel, N., & Scartezzini, J. (2007) · Energy and Buildings · doi:10.1016/j.enbuild.2007.01.018 · Cited by 643 · see citing works
A decision tree method for building energy demand modeling
Yu, Z. J., Haghighat, F., Fung, B. C. M., & Yoshino, H. (2010) · Energy and Buildings · doi:10.1016/j.enbuild.2010.04.006 · Cited by 621 · see citing works
A systematic procedure to study the influence of occupant behavior on building energy consumption
Yu, Z. J., Fung, B. C. M., Haghighat, F., Yoshino, H., & Morofsky, E. (2011) · Energy and Buildings · doi:10.1016/j.enbuild.2011.02.002 · Cited by 567 · see citing works
Discovering data mining : from concept to implementation
Cabena, P., Hadjinian, P., Stadler, R., Verhees, J., & Zanasi, A. (1998) · University of Maribor digital library (University of Maribor) · Cited by 492 · see citing works
Gunay, B., O’Brien, W., & Beausoleil-Morrison, I. (2013) · Building and Environment · doi:10.1016/j.buildenv.2013.07.020 · Cited by 286 · see citing works
A novel approach for building occupancy simulation
Wang, C., Yan, D., & Jiang, Y. (2011) · Building Simulation · doi:10.1007/s12273-011-0044-5 · Cited by 276 · see citing works
Dong, B., & Lam, K. P. (2013) · Building Simulation · doi:10.1007/s12273-013-0142-7 · Cited by 268 · see citing works
Revealing occupancy patterns in an office building through the use of occupancy sensor data
Roa, C. D., Wymelenberg, K. G. V. D., & Rieger, C. G. (2013) · Energy and Buildings · doi:10.1016/j.enbuild.2013.08.062 · Cited by 262 · see citing works
Behavioural Patterns and User Profiles related to energy consumption for heating
Guerra-Santin, O. (2011) · Energy and Buildings · doi:10.1016/j.enbuild.2011.06.024 · Cited by 256 · see citing works
Modeling occupancy in single person offices
Wang, D., Federspiel, C. C., & Rubinstein, F. (2004) · Energy and Buildings · doi:10.1016/j.enbuild.2004.06.015 · Cited by 237 · see citing works
Patterns of occupant interaction with window blinds: A literature review
Wymelenberg, K. G. V. D. (2012) · Energy and Buildings · doi:10.1016/j.enbuild.2012.05.008 · Cited by 212 · see citing works
Stochastic models for building energy prediction based on occupant behavior assessment
Virote, J., & Neves‐Silva, R. (2012) · Energy and Buildings · doi:10.1016/j.enbuild.2012.06.001 · Cited by 200 · see citing works
Yu, Z. J., Haghighat, F., Fung, B. C. M., & Zhou, L. G. (2011) · Energy and Buildings · doi:10.1016/j.enbuild.2011.12.018 · Cited by 143 · see citing works
Chang, W.-K., & Hong, T. (2013) · Building Simulation · doi:10.1007/s12273-013-0106-y · Cited by 126 · see citing works
Self-citationSun, K., Yan, D., Hong, T., & Guo, S. (2014) · Building and Environment · doi:10.1016/j.buildenv.2014.04.030 · Cited by 113 · see citing works
Self-citationPatterns of residential energy behavior
van Raaij, W. F., & Verhallen, T. M. M. (1983) · Journal of Economic Psychology · doi:10.1016/0167-4870(83)90047-8 · Cited by 110 · see citing works
An integrated approach to occupancy modeling and estimation in commercial buildings
Liao, C., & Barooah, P. (2010) · Proceedings of the ... American Control Conference/Proceedings of the American Control Conference · doi:10.1109/acc.2010.5531035 · Cited by 108 · see citing works
Methods for the prediction of intermediate activities by office occupants
Tabak, V., & de Vries, B. (2009) · Building and Environment · doi:10.1016/j.buildenv.2009.11.018 · Cited by 92 · see citing works
Stoppel, C. M., & Leite, F. L. (2013) · Energy and Buildings · doi:10.1016/j.enbuild.2013.08.042 · Cited by 73 · see citing works
OCCUPANT BEHAVIOR AND SCHEDULE PREDICTION BASED ON OFFICE APPLIANCE ENERGY CONSUMPTION DATA MINING
Zhao, J., Yun, R. J., Lasternas, B., Wang, H.-Y., Aziz, A. S., & Loftness, V. (2013) · Cited by 18 · see citing works
ACC 2015 - 2015 American Control Conference
Jiao, Q., Modares, H., Xu, S., Lewis, F. L., & Vamvoudakis, K. G. (2015) · Advances in Computing and Communications · Cited by 16 · see citing works
Flagged first, then by citations
2 of the 33 references couldn’t be matched to a known paper.
Cited by
Sorted by citations
Advances in research and applications of energy-related occupant behavior in buildings
Hong, T., Taylor-Lange, S. C., D’Oca, S., Yan, D., & Corgnati, S. P. (2015) · Energy and Buildings · doi:10.1016/j.enbuild.2015.11.052 · Cited by 543 · see citing works
Self-citationRethinking the role of occupant behavior in building energy performance: A review
Zhang, Y., Bai, X., Mills, F. P., & Pezzey, J. C. V. (2018) · Energy and Buildings · doi:10.1016/j.enbuild.2018.05.017 · Cited by 478 · see citing works
The human dimensions of energy use in buildings: A review
D’Oca, S., Hong, T., & Langevin, J. (2017) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2017.08.019 · Cited by 394 · see citing works
Self-citationA review of smart building sensing system for better indoor environment control
Dong, B., Prakash, V., Feng, F., & O’Neill, Z. D. (2019) · Energy and Buildings · doi:10.1016/j.enbuild.2019.06.025 · Cited by 369 · see citing works
Tackling climate change with machine learning
Rolnick, D., Donti, P. L., Kaack, L. H., Kochanski, K., Lacoste, A., Sankaran, K., Ross, A. S., Milojevic-Dupont, N., Jaques, N., Waldman-Brown, A., et al. (2023) · ACM Computing Surveys · doi:10.1145/3485128 · Cited by 336 · see citing works
Using machine learning techniques for occupancy-prediction-based cooling control in office buildings
Peng, Y., Rysanek, A., Nagy, Z., & Schlueter, A. (2017) · Applied Energy · doi:10.1016/j.apenergy.2017.12.002 · Cited by 334 · see citing works
Hong, T., D’Oca, S., Turner, W. J. N., & Taylor-Lange, S. C. (2015) · Building and Environment · doi:10.1016/j.buildenv.2015.02.019 · Cited by 324 · see citing works
Self-citationO’Brien, W., Wagner, A., Schweiker, M., Mahdavi, A., Day, J. K., Kjærgaard, M. B., Carlucci, S., Dong, B., Tahmasebi, F., Yan, D., et al. (2020) · Building and Environment · doi:10.1016/j.buildenv.2020.106738 · Cited by 319 · see citing works
Self-citationJia, M., Srinivasan, R. S., & Raheem, A. (2016) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2016.10.011 · Cited by 276 · see citing works
Zhang, W., Wu, Y., & Calautit, J. K. (2022) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2022.112704 · Cited by 245 · see citing works
Yang, J., Santamouris, M., & Lee, S. E. (2015) · Energy and Buildings · doi:10.1016/j.enbuild.2015.12.019 · Cited by 226 · see citing works
Stazi, F., Naspi, F., & D’Orazio, M. (2017) · Building and Environment · doi:10.1016/j.buildenv.2017.03.021 · Cited by 226 · see citing works
Diao, L., Sun, Y., Chen, Z., & Chen, J. (2017) · Energy and Buildings · doi:10.1016/j.enbuild.2017.04.072 · Cited by 214 · see citing works
Modeling occupant behavior in buildings
Carlucci, S., Simone, M. D., Firth, S. K., Kjærgaard, M. B., Markovic, R., Rahaman, M. S., Annaqeeb, M. K., Biandrate, S., Das, A., Dziedzic, J. W., et al. (2020) · Building and Environment · doi:10.1016/j.buildenv.2020.106768 · Cited by 214 · see citing works
The impacts of occupant behavior on building energy consumption: A review
Chen, S., Zhang, G., Xia, X., Chen, Y., Setunge, S., & Shi, L. X. (2021) · Sustainable Energy Technologies and Assessments · doi:10.1016/j.seta.2021.101212 · Cited by 208 · see citing works
Dai, X., Liu, J., & Zhang, X. (2020) · Energy and Buildings · doi:10.1016/j.enbuild.2020.110159 · Cited by 204 · see citing works
From big data to smart energy services: An application for intelligent energy management
Marinakis, V., Doukas, H., Tsapelas, J., Mouzakitis, S., Sicilia, Á., Madrazo, L., & Sgouridis, S. P. (2018) · Future Generation Computer Systems · doi:10.1016/j.future.2018.04.062 · Cited by 207 · see citing works
Ryu, S., & Moon, H. J. (2016) · Building and Environment · doi:10.1016/j.buildenv.2016.06.039 · Cited by 199 · see citing works
A systematic review of occupant behavior in building energy policy
Hu, S., Yan, D., Azar, E., & Guo, F. (2020) · Building and Environment · doi:10.1016/j.buildenv.2020.106807 · Cited by 184 · see citing works
Modeling occupancy and behavior for better building design and operation—A critical review
Dong, B., Yan, D., Li, Z., Jin, Y., Feng, X., & Fontenot, H. C. (2018) · Building Simulation · doi:10.1007/s12273-018-0452-x · Cited by 179 · see citing works
Paudel, S., Elmitri, M., Couturier, S., Nguyen, P. H., Kamphuis, R. I. G., Lacarrière, B., & Corre, O. L. (2016) · Energy and Buildings · doi:10.1016/j.enbuild.2016.11.009 · Cited by 174 · see citing works
An occupant behavior modeling tool for co-simulation
Hong, T., Sun, H., Chen, Y., Taylor-Lange, S. C., & Yan, D. (2015) · Energy and Buildings · doi:10.1016/j.enbuild.2015.10.033 · Cited by 169 · see citing works
Self-citationIoT and Big Data Analytics for Smart Buildings: A Survey
Daissaoui, A., Boulmakoul, A., Karim, L., & Lbath, A. (2020) · Procedia Computer Science · doi:10.1016/j.procs.2020.03.021 · Cited by 167 · see citing works
Data mining in the construction industry: Present status, opportunities, and future trends
Yan, H., Yang, N., Peng, Y., & Ren, Y. (2020) · Automation in Construction · doi:10.1016/j.autcon.2020.103331 · Cited by 161 · see citing works
Capozzoli, A., Piscitelli, M. S., Brandi, S., Grassi, D., & Chicco, G. (2018) · Energy · doi:10.1016/j.energy.2018.05.127 · Cited by 154 · see citing works
Miller, C. C., Nagy, Z., & Schlueter, A. (2017) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2017.05.124 · Cited by 153 · see citing works
Salimi, S., & Hammad, A. (2018) · Energy and Buildings · doi:10.1016/j.enbuild.2018.10.007 · Cited by 136 · see citing works
Occupancy data analytics and prediction: A case study
Liang, X. Z., Hong, T., & Shen, Q. (2016) · Building and Environment · doi:10.1016/j.buildenv.2016.03.027 · Cited by 131 · see citing works
Self-citationEstimating occupancy in heterogeneous sensor environment
Amayri, M., Arora, A., Ploix, S., Sanghamitra, B., Ngo, Q.-D., & Badarla, V. R. (2016) · Energy and Buildings · doi:10.1016/j.enbuild.2016.07.026 · Cited by 128 · see citing works
Capozzoli, A., Piscitelli, M. S., Gorrino, A., Ballarini, I., & Corrado, V. (2017) · Sustainable Cities and Society · doi:10.1016/j.scs.2017.07.016 · Cited by 128 · see citing works
Xu, X., Yu, H., Sun, Q., & Tam, V. W. Y. (2023) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2023.113396 · Cited by 125 · see citing works
Shen, W., Newsham, G. R., & Gunay, B. (2017) · Advanced Engineering Informatics · doi:10.1016/j.aei.2016.12.008 · Cited by 123 · see citing works
Yu, Z. J., Haghighat, F., & Fung, B. C. M. (2015) · Sustainable Cities and Society · doi:10.1016/j.scs.2015.12.001 · Cited by 121 · see citing works
An, J., Yan, D., & Hong, T. (2018) · Energy and Buildings · doi:10.1016/j.enbuild.2018.06.035 · Cited by 120 · see citing works
Self-citationCandanedo, L. M., Feldheim, V., & Deramaix, D. (2017) · Energy and Buildings · doi:10.1016/j.enbuild.2017.05.031 · Cited by 119 · see citing works
Occupancy learning-based demand-driven cooling control for office spaces
Peng, Y., Rysanek, A., Nagy, Z., & Schlueter, A. (2017) · Building and Environment · doi:10.1016/j.buildenv.2017.06.010 · Cited by 112 · see citing works
Cuerda, E., Guerra-Santin, O., Sendra, J. J., & Neila, F. J. (2019) · Energy and Buildings · doi:10.1016/j.enbuild.2019.109688 · Cited by 112 · see citing works
McArthur, J. J., Shahbazi, N., Fok, R., Raghubar, C., Bortoluzzi, B. S. K., & An, A. (2018) · Advanced Engineering Informatics · doi:10.1016/j.aei.2018.06.007 · Cited by 111 · see citing works
Occupant-centric urban building energy modeling: Approaches, inputs, and data sources - A review
Dabirian, S., Panchabikesan, K., & Eicker, U. (2021) · Energy and Buildings · doi:10.1016/j.enbuild.2021.111809 · Cited by 107 · see citing works
Occupancy sensing in buildings: A review of data analytics approaches
Saha, H., Florita, A. R., Henze, G. P., & Sarkar, S. (2019) · Energy and Buildings · doi:10.1016/j.enbuild.2019.02.030 · Cited by 99 · see citing works
Review on occupancy detection and prediction in building simulation
Ding, Y. Y., Han, S., Tian, Z., Yao, J., Chen, W., & Zhang, Q. (2021) · Building Simulation · doi:10.1007/s12273-021-0813-8 · Cited by 97 · see citing works
Predictability of occupant presence and performance gap in building energy simulation
Ahn, K.-U., Kim, D.-W., Park, C.-S., & de Wilde, P. (2017) · Applied Energy · doi:10.1016/j.apenergy.2017.04.083 · Cited by 97 · see citing works
Development of building energy saving advisory: A data mining approach
Ashouri, M., Haghighat, F., Fung, B. C. M., Lazrak, A., & Yoshino, H. (2018) · Energy and Buildings · doi:10.1016/j.enbuild.2018.04.052 · Cited by 96 · see citing works
Wang, Y., & Shao, L. (2016) · Building and Environment · doi:10.1016/j.buildenv.2016.12.015 · Cited by 95 · see citing works
Typical occupancy profiles and behaviors in residential buildings in the United States
Mitra, D., Steinmetz, N., Chu, Y., & Cetin, K. S. (2019) · Energy and Buildings · doi:10.1016/j.enbuild.2019.109713 · Cited by 93 · see citing works
Uddin, M. N., Wei, H.-H., Chi, H.-L., & Ni, M. (2021) · Buildings · doi:10.3390/buildings11020041 · Cited by 93 · see citing works
Laaroussi, Y., Bahrar, M., Mankibi, M. E., Draoui, A., & Larbi, A. S. (2020) · Sustainable Cities and Society · doi:10.1016/j.scs.2020.102420 · Cited by 92 · see citing works
A preliminary study of representing the inter-occupant diversity in occupant modelling
O’Brien, W., Gunay, B., Tahmasebi, F., & Mahdavi, A. (2016) · Journal of Building Performance Simulation · doi:10.1080/19401493.2016.1261943 · Cited by 91 · see citing works
Occupancy data at different spatial resolutions: Building energy performance and model calibration
Chong, A., Augenbroe, G., & Yan, D. (2021) · Applied Energy · doi:10.1016/j.apenergy.2021.116492 · Cited by 89 · see citing works
Salcido, J. C., Raheem, A., & Issa, R. R. A. (2016) · Energy and Buildings · doi:10.1016/j.enbuild.2016.06.054 · Cited by 88 · see citing works
Building occupancy forecasting: A systematical and critical review
Jin, Y., Yan, D., Chong, A., Dong, B., & An, J. (2021) · Energy and Buildings · doi:10.1016/j.enbuild.2021.111345 · Cited by 90 · see citing works
State of the art review on the HVAC occupant-centric control in different commercial buildings
Huang, G., Ng, S. T., Li, D., & Zhang, Y. (2024) · Journal of Building Engineering · doi:10.1016/j.jobe.2024.110445 · Cited by 89 · see citing works
O’Neill, Z. D., & Niu, F. (2017) · Building and Environment · doi:10.1016/j.buildenv.2017.01.025 · Cited by 85 · see citing works
Wang, W., Chen, J., & Song, X. (2017) · Building and Environment · doi:10.1016/j.buildenv.2017.08.003 · Cited by 85 · see citing works
Dong, J., Winstead, C., Nutaro, J. J., & Kuruganti, T. P. (2018) · Energies · doi:10.3390/en11092427 · Cited by 83 · see citing works
Occupant-centered real-time control of indoor temperature using deep learning algorithms
Jung, S., Jeoung, J., & Hong, T. (2021) · Building and Environment · doi:10.1016/j.buildenv.2021.108633 · Cited by 81 · see citing works
Self-citationMixed methods approach to determine occupants’ behaviour – Analysis of two case studies
Guerra-Santin, O., Romero, N. A., Cuerda, E., & Keyson, D. V. (2016) · Energy and Buildings · doi:10.1016/j.enbuild.2016.08.084 · Cited by 78 · see citing works
Towards occupant-centric simulation-aided building design: a case study
Abuimara, T., O’Brien, W., Gunay, B., & Carrizo, J. S. (2019) · Building Research & Information · doi:10.1080/09613218.2019.1652550 · Cited by 78 · see citing works
Development of an occupancy learning algorithm for terminal heating and cooling units
Gunay, B., O’Brien, W., & Beausoleil-Morrison, I. (2015) · Building and Environment · doi:10.1016/j.buildenv.2015.06.009 · Cited by 78 · see citing works
Development of Dutch occupancy and heating profiles for building simulation
Guerra-Santin, O., & Silvester, S. (2016) · Building Research & Information · doi:10.1080/09613218.2016.1160563 · Cited by 77 · see citing works
Yang, T., Bandyopadhyay, A., O’Neill, Z. D., Wen, J., & Dong, B. (2021) · Building Simulation · doi:10.1007/s12273-021-0861-0 · Cited by 80 · see citing works
Zhou, X., Yan, D., Feng, X., Deng, G., Jian, Y., & Jiang, Y. (2016) · Building Simulation · doi:10.1007/s12273-016-0280-9 · Cited by 77 · see citing works
Data mining of space heating system performance in affordable housing
Ren, X., Yan, D., & Hong, T. (2015) · Building and Environment · doi:10.1016/j.buildenv.2015.02.009 · Cited by 76 · see citing works
Self-citationA new modeling approach for short-term prediction of occupancy in residential buildings
Li, Z., & Dong, B. (2017) · Building and Environment · doi:10.1016/j.buildenv.2017.05.005 · Cited by 74 · see citing works
Pan, S., Wang, X., Wei, Y., Zhang, X., Gál, C., Ren, G., Yan, D., Shi, Y., Wu, J., Xia, L., et al. (2017) · Building Simulation · doi:10.1007/s12273-017-0377-9 · Cited by 73 · see citing works
Ahmed, O., Sezer, N., Ouf, M. M., Wang, L. L., & Hassan, I. G. (2023) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2023.113558 · Cited by 73 · see citing works
Fathalian, A., & Kargarsharifabad, H. (2018) · Case Studies in Thermal Engineering · doi:10.1016/j.csite.2018.06.007 · Cited by 73 · see citing works
Zikos, S., Tsolakis, A. C., Meskos, D., Tryferidis, A., & Tzovaras, D. K. (2016) · Automation in Construction · doi:10.1016/j.autcon.2016.05.005 · Cited by 71 · see citing works
Extracting typical occupancy data of different buildings from mobile positioning data
Gu, J., Xu, P., Pang, Z., Chen, Y., Ji, Y., & Chen, Z. (2018) · Energy and Buildings · doi:10.1016/j.enbuild.2018.09.002 · Cited by 71 · see citing works
Correlation between occupants and energy consumption
Ahn, K.-U., & Park, C.-S. (2016) · Energy and Buildings · doi:10.1016/j.enbuild.2016.01.010 · Cited by 71 · see citing works
Omrany, H., Al-Obaidi, K. M., Hossain, M., Alduais, N. A. M., Al-Duais, H. S., & Ghaffarianhoseini, A. (2024) · Discover Cities · doi:10.1007/s44327-024-00002-w · Cited by 84 · see citing works
Boodi, A., Beddiar, K., Benamour, M., Amirat, Y., & Benbouzid, M. (2018) · Energies · doi:10.3390/en11102604 · Cited by 69 · see citing works
Performance evaluation of an agent-based occupancy simulation model
Luo, X., Lam, K. P., Chen, Y., & Hong, T. (2017) · Building and Environment · doi:10.1016/j.buildenv.2017.01.015 · Cited by 67 · see citing works
Self-citationPang, Z., Xu, P., O’Neill, Z. D., Gu, J., Qiu, S., Lu, X., & Li, X. (2018) · Building and Environment · doi:10.1016/j.buildenv.2018.05.030 · Cited by 68 · see citing works
Energy-Related Occupant Behaviour and Its Implications in Energy Use: A Chronological Review
Tam, V. W. Y., Almeida, L. M. M. C. E., & Le, K. N. (2018) · Sustainability · doi:10.3390/su10082635 · Cited by 64 · see citing works
The influence of personality traits on occupant behavioural patterns
Schweiker, M., Hawighorst, M., & Wagner, A. (2016) · Energy and Buildings · doi:10.1016/j.enbuild.2016.09.019 · Cited by 63 · see citing works
Probabilistic behavioral modeling in building performance simulation: A Monte Carlo approach
Cecconi, F. R., Manfren, M., Tagliabue, L. C., Ciribini, A. L. C., & Angelis, E. D. (2017) · Energy and Buildings · doi:10.1016/j.enbuild.2017.05.013 · Cited by 61 · see citing works
Jia, M., Srinivasan, R. S., Ries, R. J., Weyer, N., & Bharathy, G. K. (2019) · Energy and Buildings · doi:10.1016/j.enbuild.2019.07.009 · Cited by 60 · see citing works
Advancing manufacturing systems with big-data analytics: A conceptual framework
Kozjek, D., Vrabič, R., Rihtaršič, B., Nada Lavrač, A., & Butala, P. (2020) · International Journal of Computer Integrated Manufacturing · doi:10.1080/0951192x.2020.1718765 · Cited by 60 · see citing works
Probabilistic behavioural modeling in building performance simulation—The Brescia eLUX lab
Tagliabue, L. C., Manfren, M., Ciribini, A. L. C., & Angelis, E. D. (2016) · Energy and Buildings · doi:10.1016/j.enbuild.2016.06.083 · Cited by 59 · see citing works
Wei, Y., Yu, H., Pan, S., Xia, L., Xie, J., Wang, X., Wu, J., Zhang, W., & Li, Q. (2019) · Building and Environment · doi:10.1016/j.buildenv.2019.04.040 · Cited by 59 · see citing works
Li, Z., & Dong, B. (2017) · Energy and Buildings · doi:10.1016/j.enbuild.2017.09.052 · Cited by 59 · see citing works
Muroni, A., Gaetani, I., Hoes, P.-J., & Hensen, J. J. (2019) · Building Simulation · doi:10.1007/s12273-019-0573-x · Cited by 59 · see citing works
Context-specific urban occupancy modeling using location-based services data
Happle, G., Fonseca, J. A., & Schlueter, A. (2020) · Building and Environment · doi:10.1016/j.buildenv.2020.106803 · Cited by 58 · see citing works
A study on temperature-setting behavior for room air conditioners based on big data
Yan, L. H., Liu, M., Xue, K., & Zhang, Z. (2020) · Journal of Building Engineering · doi:10.1016/j.jobe.2020.101197 · Cited by 57 · see citing works
Micolier, A., Taillandier, F., Taillandier, P., & Bos, F. (2019) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2019.03.008 · Cited by 56 · see citing works
Panchabikesan, K., Haghighat, F., & Mankibi, M. E. (2020) · Energy · doi:10.1016/j.energy.2020.119539 · Cited by 56 · see citing works
Building occupancy number prediction: A Transformer approach
Sun, K., Qaisar, I., Khan, M. A., Xing, T., & Zhao, Q. (2023) · Building and Environment · doi:10.1016/j.buildenv.2023.110807 · Cited by 55 · see citing works
Human-building interaction at work: Findings from an interdisciplinary cross-country survey in Italy
D’Oca, S., Pisello, A. L., Simone, M. D., Barthelmes, V. M., Hong, T., & Corgnati, S. P. (2018) · Building and Environment · doi:10.1016/j.buildenv.2018.01.039 · Cited by 55 · see citing works
Self-citationKampezidou, S. I., Ray, A. T., Duncan, S. J., Balchanos, M. G., & Mavris, D. N. (2021) · Energy and Buildings · doi:10.1016/j.enbuild.2021.110863 · Cited by 54 · see citing works
Analyzing energy consumption patterns of an educational building through data mining
Alam, M., & Devjani, M. R. (2021) · Journal of Building Engineering · doi:10.1016/j.jobe.2021.103385 · Cited by 53 · see citing works
Occupancy-based buildings-to-grid integration framework for smart and connected communities
Dong, B., Li, Z., Taha, A. F., & Gatsis, N. (2018) · Applied Energy · doi:10.1016/j.apenergy.2018.03.007 · Cited by 52 · see citing works
Roselyn, J. P., Uthra, R. A., Raj, A., Devaraj, D., Bharadwaj, P., & Kaki, S. V. D. K. (2018) · Sustainable Cities and Society · doi:10.1016/j.scs.2018.09.031 · Cited by 52 · see citing works
Modelling occupant behaviour in residential buildings: A systematic literature review
Mylonas, A., Tsangrassoulis, A., & Pascual, J. (2024) · Building and Environment · doi:10.1016/j.buildenv.2024.111959 · Cited by 51 · see citing works
Rouchier, S. (2018) · Energy and Buildings · doi:10.1016/j.enbuild.2018.02.009 · Cited by 50 · see citing works
Miller, C. C. (2019) · Energy and Buildings · doi:10.1016/j.enbuild.2019.07.019 · Cited by 50 · see citing works
Cuerda, E., Guerra-Santin, O., Sendra, J. J., & González, F. J. N. (2019) · Building Simulation · doi:10.1007/s12273-019-0539-z · Cited by 49 · see citing works
Yang, X., Hu, M., Heeren, N., Zhang, C., Verhagen, T. J., Tukker, A., & Steubing, B. R. P. (2020) · Applied Energy · doi:10.1016/j.apenergy.2020.115953 · Cited by 48 · see citing works
Newsham, G. R., Xue, H., Arsenault, C. D., Valdés, J. J., Burns, G. J., Scarlett, E., Kruithof, S. G., & Shen, W. (2016) · Energy and Buildings · doi:10.1016/j.enbuild.2016.11.029 · Cited by 47 · see citing works
Suitability analysis of modeling and assessment approaches in energy efficiency in buildings
Koulamas, C., Kalogeras, A. P., Pacheco-Torres, R., Casillas, J., & Ferrarini, L. (2017) · Energy and Buildings · doi:10.1016/j.enbuild.2017.12.002 · Cited by 52 · see citing works
- Authors
- D’Oca, S., & Hong, T.
- Affiliations
- Lawrence Berkeley National Laboratory (US)
- Corresponding author
- Hong, Tianzhen
- Venue
- Energy and Buildings
- Publisher
- Elsevier BV
- Published
- 2015-02
- Volume
- 88
- Pages
- 395-408
- ISSN
- 0378-7788 (ISSN-L)
- OpenAlex
- W1981885501
- Cited by
- 294
- References
- 33
- Citations by year
- 2026: 12 · 2025: 17 · 2024: 17 · 2023: 26 · 2022: 27 · 2021: 33 · 2020: 32 · 2019: 25 · 2018: 36 · 2017: 31 · 2016: 26 · 2015: 12
- FWCI
- 31.81
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Energy and Buildings (acceptedVersion)
- OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (submittedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- U.S. Department of Energy (DE-AC02-05CH11231)
- U.S.-China Clean Energy Research Center
- Topics
- Physical Sciences › Engineering › Building and Construction › Building Energy and Comfort Optimization
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Smart Grid Energy Management
- Physical Sciences › Computer Science › Information Systems › Data Mining and Machine Learning Applications
- Keywords
- building occupancy, occupancy schedules, office buildings, occupancy patterns, building energy simulation, decision tree, rule induction, clustering, occupant behavior, human-building interaction
About these checks
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.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review