Occupant behavior and schedule modeling for building energy simulation through office appliance power consumption data mining

Support-vector networks

Cortes, C., & Vapnik, V. (1995) · Machine Learning · doi:10.1007/bf00994018 · Cited by 59,421

Support-Vector Networks

Cortes, C., & Vapnik, V. N. (1995) · Machine Learning · doi:10.1023/a:1022627411411 · Cited by 34,565

Data Mining: Practical Machine Learning Tools and Techniques

Witten, I. H., Frank, E., & Hall, M. A. (2011) · Elsevier eBooks · doi:10.1016/c2009-0-19715-5 · Cited by 25,543

Untitled work

(1992) · Cited by 23,431

A training algorithm for optimal margin classifiers

Boser, B. E., Guyon, I. M., & Vapnik, V. N. (1992) · Proceedings of the fifth annual workshop on Computational learning theory · doi:10.1145/130385.130401 · Cited by 11,992

Robust Locally Weighted Regression and Smoothing Scatterplots

Cleveland, W. S. (1979) · Journal of the American Statistical Association · doi:10.1080/01621459.1979.10481038 · Cited by 11,594

Support Vector Regression Machines

Drucker, H., Burges, C. J. C., Kaufman, L., Smola, A. J., & Vapnik, V. N. (1996) · Cited by 4,666

Supervised Machine Learning: A Review of Classification Techniques

Kotsiantis, S. B. (2007) · Informatica · Cited by 4,192

Survey of Wireless Indoor Positioning Techniques and Systems

Liu, H., Darabi, H., Banerjee, P. P., & Liu, J. (2007) · IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews) · doi:10.1109/tsmcc.2007.905750 · Cited by 4,184

Untitled work

(1998) · Cited by 2,679

Assessing Agreement on Classification Tasks: The Kappa Statistic

Carletta, J. (1996) · arXiv · doi:10.48550/arxiv.cmp-lg/9602004 · Cited by 2,088

A survey of indoor positioning systems for wireless personal networks

Gu, Y., Lo, A., & Niemegeers, I. G. M. M. (2009) · IEEE Communications Surveys & Tutorials · doi:10.1109/surv.2009.090103 · Cited by 1,564

Applying support vector machines to predict building energy consumption in tropical region

Dong, B., Cao, C., & Lee, S. E. (2004) · Energy and Buildings · doi:10.1016/j.enbuild.2004.09.009 · Cited by 803

The dark side of occupants’ behaviour on building energy use

Masoso, O. T., & Grobler, L. J. (2009) · Energy and Buildings · doi:10.1016/j.enbuild.2009.08.009 · Cited by 684

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

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

Python Programming Language.

van Rossum, G. (2006) · USENIX Annual Technical Conference · Cited by 581

Locally Weighted Learning for Control

Atkeson, C. G., Moore, A., & Schaal, S. (1997) · Artificial Intelligence Review · doi:10.1023/a:1006511328852 · Cited by 554

Motivating energy conservation in the workplace: An evaluation of the use of group-level feedback and peer education

Carrico, A. R., & Riemer, M. (2010) · Journal of Environmental Psychology · doi:10.1016/j.jenvp.2010.11.004 · Cited by 489

Applying support vector machine to predict hourly cooling load in the building

Li, Q., Meng, Q., Cai, J., Yoshino, H., & Mochida, A. (2009) · Applied Energy · doi:10.1016/j.apenergy.2008.11.035 · Cited by 485

Accuracy of iPhone Locations: A Comparison of Assisted GPS, WiFi and Cellular Positioning

Zandbergen, P. A. (2009) · Transactions in GIS · doi:10.1111/j.1467-9671.2009.01152.x · Cited by 444

Coordinating occupant behavior for building energy and comfort management using multi-agent systems

Klein, L., Kwak, J.-Y., Kavulya, G., Jazizadeh, F., Becerik-Gerber, B., Varakantham, P. R., & Tambe, M. (2011) · Automation in Construction · doi:10.1016/j.autcon.2011.11.012 · Cited by 369

A model of satisfaction with open-plan office conditions: COPE field findings

Veitch, J. A., Charles, K., Farley, K. M. J., & Newsham, G. R. (2007) · Journal of Environmental Psychology · doi:10.1016/j.jenvp.2007.04.002 · Cited by 338

Thermal comfort: use of controls in naturally ventilated buildings

Raja, I. A., Nicol, F., McCartney, K. J., & Humphreys, M. (2001) · Energy and Buildings · doi:10.1016/s0378-7788(00)00087-6 · Cited by 305

Locally Weighted Naive BayesPreprint

Frank, E., Hall, M., & Pfahringer, B. (2012) · arXiv (Cornell University) · doi:10.48550/arxiv.1212.2487 · Cited by 295

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

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

A personalized measure of thermal comfort for building controls

Daum, D., Haldi, F., & Morel, N. (2010) · Building and Environment · doi:10.1016/j.buildenv.2010.06.011 · Cited by 204

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

Simulating multiple occupant behaviors in buildings: An agent-based modeling approach

Lee, Y. S., & Malkawi, A. M. (2013) · Energy and Buildings · doi:10.1016/j.enbuild.2013.11.020 · Cited by 198

A method for the identification and modelling of realistic domestic occupancy sequences for building energy demand simulations and peer comparison

Aerts, D., Minnen, J., Glorieux, I., Wouters, I., & Descamps, F. (2014) · Building and Environment · doi:10.1016/j.buildenv.2014.01.021 · Cited by 198

Modeling a ground-coupled heat pump system by a support vector machine

Esen, H., İnallı, M., Şengür, A., & Esen, M. (2007) · Renewable Energy · doi:10.1016/j.renene.2007.09.025 · Cited by 191

Positioning with Bluetooth

Hallberg, J., Nilsson, M., & Synnes, K. (2003) · doi:10.1109/ictel.2003.1191568 · Cited by 170

Agent-based and graphical modelling of building occupancy

Liao, C., Lin, Y., & Barooah, P. (2011) · Journal of Building Performance Simulation · doi:10.1080/19401493.2010.531143 · Cited by 150

Python (programming language)

Gajera, J., Campos, A., & Weerakkody, Y. (2019) · Radiopaedia.org · doi:10.53347/rid-71005 · Cited by 148

Proceedings of the 17th Conference in Uncertainty in Artificial Intelligence

Breese, J., & Koller, D. (2001) · Cited by 135

Building energy and comfort management through occupant behaviour pattern detection based on a large-scale environmental sensor network

Dong, B., & Lam, K. P. (2011) · Journal of Building Performance Simulation · doi:10.1080/19401493.2011.577810 · Cited by 132

Impact of occupant's actions on energy building performance and thermal sensation

Bonte, M., Thellier, F., & Lartigue, B. (2014) · Energy and Buildings · doi:10.1016/j.enbuild.2014.02.068 · Cited by 116

Field experiments on energy consumption and thermal comfort in the office environment controlled by occupants’ requirements from PC terminal

Murakami, Y., Terano, M., Mizutani, K., Harada, M., & Kuno, S. (2006) · Building and Environment · doi:10.1016/j.buildenv.2006.05.012 · Cited by 107

Occupant Behavior: Impact onEnergy Use of Private Offices

Hong, T. (2013) · Cited by 101

A robust occupancy detection and tracking algorithm for the automatic monitoring and commissioning of a building

Shih, H.-C. (2014) · Energy and Buildings · doi:10.1016/j.enbuild.2014.03.069 · Cited by 95

Extracting knowledge from building-related data — A data mining framework

Yu, Z. J., Fung, B. C. M., & Haghighat, F. (2013) · Building Simulation · doi:10.1007/s12273-013-0117-8 · Cited by 84

A methodology for peak energy requirement considering actual variation of occupants’ behavior schedules

Tanimoto, J., Hagishima, A., & Sagara, H. (2006) · Building and Environment · doi:10.1016/j.buildenv.2006.06.034 · Cited by 82

Occupant Behavior: Impact on Energy Use of Private Offices

Hong, T. L. (2016) · OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) · Cited by 77

Integrating probabilistic methods for describing occupant presence with building energy simulation models

Stoppel, C. M., & Leite, F. L. (2013) · Energy and Buildings · doi:10.1016/j.enbuild.2013.08.042 · Cited by 73

Information-theoretic environment features selection for occupancy detection in open office spaces

Zhang, R., Lam, K. P., Chiou, Y. S., & Dong, B. (2012) · Building Simulation · doi:10.1007/s12273-012-0075-6 · Cited by 68

White LED ceiling lights positioning systems for optical wireless indoor applications

Hann, S., Kim, J., Jung, S.-Y., & Park, C.-S. (2010) · European Conference on Optical Communication · doi:10.1109/ecoc.2010.5621490 · Cited by 66

The value of post-occupancy evaluation for building occupants and facility managers

Loftness, V., Aziz, A., Choi, J.-H., Kampschroer, K., Powell, K. M., Atkinson, M., & HEERWAGEN, J. H. (2009) · Intelligent Buildings International · doi:10.3763/inbi.2009.si04 · Cited by 65

Sustainability in the Workplace: Nine Intervention Techniques for Behavior Change

Yun, R. J., Scupelli, P. G., Aziz, A., & Loftness, V. (2013) · Lecture notes in computer science · doi:10.1007/978-3-642-37157-8_30 · Cited by 57

Linking occupant complaints to building performance

Goins, J., & Moezzi, M. (2012) · Building Research & Information · doi:10.1080/09613218.2013.763714 · Cited by 57

The Concept of Total Building Performance and Building Diagnostics

Hartkopf, V., Loftness, V., & Mill, P. (1986) · doi:10.1520/stp23009s · Cited by 50

Toward the Design of a Dashboard to Promote Environmentally Sustainable Behavior among Office Workers

Yun, R. J., Lasternas, B., Aziz, A., Loftness, V., Scupelli, P. G., Rowe, A., Kothari, R., Marion, F. A., & Zhao, J. (2013) · Lecture notes in computer science · doi:10.1007/978-3-642-37157-8_29 · Cited by 39

Influential factors analysis on LEED building markets in U.S. East Coast cities by using Support Vector Regression

Zhao, J., & Lam, K. P. (2012) · Sustainable Cities and Society · doi:10.1016/j.scs.2012.05.009 · Cited by 36

The value of post-occupancy evaluation for building occupants and facility managers

Loftness, V., Aziz, A., Choi, J.-H., et al. (2009) · Intelligent Buildings International · doi:10.3763/inbi.2009.si04/splitsection3 · Cited by 36

Thermal and behavioral modeling of occupant-controlled heating, ventilating and air conditioning systems

Glicksman, L. R., & Taub, S. C. (1997) · Energy and Buildings · doi:10.1016/s0378-7788(96)01019-5 · Cited by 34

Building Performance: Function, Preservation, and Rehabilitation

Davis, G. E. (1986) · doi:10.1520/stp901-eb · Cited by 34

Locally Weighted Regression

Kakade, S. M., & Shakhnarovich, G. (2009) · Cited by 30

CoBi: Bio-Sensing Building Mechanical System Controls for Sustainably Enhancing Individual Thermal Comfort

Choi, J. H. (2010) · KiltHub Repository · doi:10.1184/r1/6715145 · Cited by 26

Forecasting Energy Demand in Large Commercial Buildings Using Support Vector Machine Regression

Solomon, D. M., Winter, R. L., Boulanger, A., Anderson, R. N., & Wu, L. (2011) · doi:10.7916/d85d90x7 · Cited by 26

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

Living Building Challenge

International Living Future Institute, U. (2012) · Journal of Education for Sustainable Development · doi:10.1177/0973408213475380c · Cited by 17

Building America Best Practices Series - High-Performance Home Technologies: Guide to Determining Climate Regions by County (Volume 7.2, Rev. 2)

Energy Efficiency Office. Building Technologies Office USDOE Office of Energy Efficiency and Renewable Energy (EERE), Baechler, M. C., Gilbride, T. L., Cole, P., Hefty, M. G., & Ruiz, K. (2013) · doi:10.2172/1217886 · Cited by 15

The intuitive control of smart home and office environments

Peters, S., Loftness, V., & Hartkopf, V. (2011) · doi:10.1145/2048237.2048255 · Cited by 9

Post-occupancy evaluation for energy conservation, superior IEQ & increased occupant satisfaction

Park, J., Aziz, A., & Loftness, V. (2013) · SHURA (Sheffield Hallam University Research Archive) (Sheffield Hallam University) · Cited by 9

The Impacts of Real-time Knowledge Based Personal Lighting Control on Energy Consumption, User Satisfaction and Task Performance in Offices

Gu, Y. Q. (2018) · Figshare · doi:10.1184/r1/6723614.v1 · Cited by 8

The Impacts of Real-time Knowledge Based Personal Lighting Control on Energy Consumption, User Satisfaction and Task Performance in Offices

Gu, Y. (2011) · Figshare · doi:10.1184/r1/6723614 · Cited by 8

Proceedings of the 10th SIGPLAN symposium on New ideas, new paradigms, and reflections on programming and software

(2011) · doi:10.1145/2048237 · Cited by 7

Smart Power Strip

Sorensen, S. (2013) · MSU Student Research Celebration · Cited by 1

The impact of occupants’ behaviours on building energy analysis: A research review

Delzendeh, E., Wu, S., Lee, A. H.-C., & Zhou, Y. (2017) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2017.05.264 · Cited by 593

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

Towards sustainable, energy-efficient and healthy ventilation strategies in buildings: A review

Chenari, B., Carrilho, J. D., & da Silva, M. G. (2016) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2016.01.074 · Cited by 517

IEA EBC Annex 66: Definition and simulation of occupant behavior in buildings

Yan, D., Hong, T., Dong, B., Mahdavi, A., D’Oca, S., Gaetani, I., & Feng, X. (2017) · Energy and Buildings · doi:10.1016/j.enbuild.2017.09.084 · Cited by 509

Rethinking 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

OCCUPANT BEHAVIOR AND SCHEDULE PREDICTION BASED ON OFFICE APPLIANCE ENERGY CONSUMPTION DATA MINING

(2016)

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

Occupancy schedules learning process through a data mining framework

D’Oca, S., & Hong, T. (2015) · Energy and Buildings · doi:10.1016/j.enbuild.2014.11.065 · Cited by 294

Data driven occupancy information for energy simulation and energy use assessment in residential buildings

Panchabikesan, K., Haghighat, F., & Mankibi, M. E. (2020) · Energy · doi:10.1016/j.energy.2020.119539 · Cited by 56

Data Mining of Occupant Behavior in Office Buildings

D’Oca, S., Corgnati, S. P., & Hong, T. (2015) · Energy Procedia · doi:10.1016/j.egypro.2015.11.022 · Cited by 30