Occupants Behavior Research Bibliography

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X. Guo, Tiller, D. K., Henze, G. P., and Waters, C. E., The performance of occupancy-based lighting control systems: A review, Lighting Research & Technology, vol. 42, pp. 415-431, 2010.
S. Guo, Yan, D., Peng, C., Cui, Y., Zhou, X., and Hu, S., Investigation and analyses of residential heating in the HSCW climate zone of China: Status quo and key features, Building and Environment, vol. 94, pp. 532-542, 2015.
B. H. Gunay, O'Brien, W., and Beausoleil-Morrison, I., A critical review of observation studies, modeling, and simulation of adaptive occupant behaviors in offices, Building and Environment, vol. 70, pp. 31-47, 2013.
B. Gunay, O'Brien, W. L., Beausoleil-Morrison, I., D'Oca, S., and Corgnati, S. P., On modelling and simulation of occupant models, in Building Simulation Conference, Hyderabad, India, 2015.
B. H. Gunay, O'Brien, W., Beausoleil-Morrison, I., and Huchuk, B., On adaptive occupant-learning window blind and lighting controls, Building Research & Information, vol. 7, no. 6, pp. 739-756, 2014.
B. H. Gunay, O'Brien, W., Beausoleil-Morrison, I., Goldstein, R., Breslav, S., and Khan, A., Coupling stochastic occupant models to building performance simulation using the discrete event system specification formalism, Journal of Building Performance Simulation, vol. 7, pp. 457-478, 2014.
R. Gulbinas and Taylor, J., Effects of real-time eco-feedback and organizational network dynamics on energy efficient behavior in commercial buildings, Energy and Buildings, vol. 84, pp. 493-500, 2014.
R. Gulbinas, Jain, R., Taylor, J., Peschiera, G., and Golparvar-Fard, M., Network eco-informatics: Development of a social eco-feedback system to drive energy efficiency in residential buildings, ASCE Journal of Computing in Civil Engineering, vol. 28, pp. 89-98, 2014.
R. Gulbinas, Jain, R., and Taylor, J., BizWatts: A modular socio-technical energy management system for empowering commercial building occupants to conserve energy, Applied Energy, vol. 136, pp. 1076–1084, 2014.
R. Gulbinas, Khosrowpour, A., and Taylor, J., Segmentation and Classification of Commercial Building Occupants by Energy-Use Efficiency and Predictability, IEEE Transactions on Smart Grid, vol. 6, 3 vol. pp. 1414-1424, 2015.
A. Guillemin and Molteni, S., An energy-efficient controller for shading devices self-adapting to the user wishes, Building and Environment, vol. 37, pp. 1091-1097, 2002.
O. Guerra-Santin and Itard, L., Occupants' behaviour: determinants and effects on residential heating consumption, Building Research & Information, vol. 38, pp. 318-338, 2010.
E. Gratia and De Herde, A., Design of low energy office buildings, Energy and Buildings, vol. 35, pp. 473-491, 2003.
K. Gram-Hanssen, Households' energy use - Which is the more important: efficient technologies or user practices?, pp. 992-999, 2011.
K. Gram-Hanssen, Residential heat comfort practices: understanding users, Building Research & InformationBuilding Research & Information, vol. 38, pp. 175-186, 2010.
S. Goyal, Ingley, H. A., and Barooah, P., Occupancy-based zone-climate control for energy-efficient buildings: Complexity vs. performance, Applied Energy, vol. 106, pp. 209-221, 2013.
B. Givoni, Characteristics, design implicaitons, and applicability of passive solar heating-systems for buildings , Solar Energy, vol. 47, pp. 425-435, 1991.
Z. M. Gill, Tierney, M. J., Pegg, I. M., and Allan, N., Measured energy and water performance of an aspiring low energy/carbon affordable housing site in the UK, Energy and Buildings, vol. 43, pp. 117-125, 2011.
N. Ghiassi, Tahmasebi, F., and Mahdavi, A., Harnessing buildings’ operational diversity in a computational framework for high-resolution urban energy modeling, Building Simulation, pp. 1-17, 2017.
A. Ghahramani, Jazizadeh, F., and Becerik-Gerber, B., A Knowledge Based Approach for Selecting Energy- Aware and Comfort-Driven HVAC Temperature Set Points, Journal of Energy and Buildings, vol. 85, pp. 536-548, 2014.
A. Ghahramani, Tang, C., and Becerik-Gerber, B., An Online Learning Approach for Quantifying Personalized Thermal Comfort via Adaptive Stochastic Modeling, Journal of Building and Environment, vol. 92, pp. 86-96, 2015.
S. Gauthier, Aragon, V., James, P., and Anderson, B., Occupancy Patterns Scoping Review Project, Department for Business, Energy & Industrial Strategy, University of Southampton, 2016.
L. M. Gartland, Emery, A. F., Sun, Y. S., and Kippenhan, C. J., Residential energy usage and the influence of cooupant behavior, ASME Winter annual meeting, New Orleans, Louisiana. 1993.
V. Garg and Bansal, N. K., Smart occupancy sensors to reduce energy consumption, Energy and Buildings, vol. 32, pp. 81-87, 2000.
R. Galvin, Targeting ‘behavers’ rather than behaviours: A ‘subject-oriented’ approach for reducing space heating rebound effects in low energy dwellings, Energy and Buildings, vol. 67, pp. 596-607, 2013.
A. D. Galasiu and Veitch, J. A., Occupant preferences and satisfaction with the luminous environment and control systems in daylit offices: a literature review, Energy and Buildings, vol. 38, pp. 728-742, 2006.
A. D. Galasiu, Newsham, G. R., Suvagau, C., and Sander, D. M., Energy saving lighting control systems for open-plan offices: A field study, Leukos, vol. 4, pp. 7-29, 2007.
I. Gaetani, Hoes, P. - J., and Hensen, J. L., Occupant behavior in building energy simulation: towards a fit-for-purpose modeling strategy, Energy and Buildings, vol. 121, pp. 188-204, 2016.
I. Gaetani, Hoes, P. - J., and Hensen, J. L., On the sensitivity to different aspects of occupant behaviour for selecting the appropriate modelling complexity in building performance predictions, Journal of Building Performance Simulation, pp. 1-11, 2016.
R. Gade, Jorgensen, A., and Moeslund, T. B., Long-term occupancy analysis using graph-based optimisation in thermal imagery, Computer Vision and Pattern Recognition (CVPR), 2013 IEEE Conference on. Portland, OR, pp. 3698-3705, 2013.