Occupancy learning-based demand-driven cooling control for office spaces
暂无分享,去创建一个
Zoltán Nagy | Adam Rysanek | Arno Schlüter | Yuzhen Peng | Z. Nagy | A. Rysanek | Yuzhen Peng | A. Schlüter
[1] H. Mirinejad,et al. A review of intelligent control techniques in HVAC systems , 2012, 2012 IEEE Energytech.
[2] W Wim Zeiler,et al. Occupancy measurement in commercial office buildings for demand-driven control applications : a survey and detection system evaluation , 2015 .
[3] H. B. Gunay,et al. Development of an occupancy learning algorithm for terminal heating and cooling units , 2015 .
[4] Alberto Cerpa,et al. Occupancy based demand response HVAC control strategy , 2010, BuildSys '10.
[5] Silvia Santini,et al. Predicting household occupancy for smart heating control: A comparative performance analysis of state-of-the-art approaches , 2014 .
[6] James E. Braun,et al. Reducing energy costs and peak electrical demand through optimal control of building thermal storage , 1990 .
[7] John Krumm,et al. PreHeat: controlling home heating using occupancy prediction , 2011, UbiComp '11.
[8] Arno Schlueter,et al. Occupant centered lighting control for comfort and energy efficient building operation , 2015 .
[9] Bing Dong,et al. Sensor-based occupancy behavioral pattern recognition for energy and comfort management in intelligent buildings , 2009 .
[10] David J. C. MacKay,et al. Information Theory, Inference, and Learning Algorithms , 2004, IEEE Transactions on Information Theory.
[11] J. H. Eto. A COMPARISON OF WEATHER NORMALIZATION TECHNIQUES FOR COMMERICAL BUILDING ENERGY USE , 1985 .
[12] Tuan Anh Nguyen,et al. Energy intelligent buildings based on user activity: A survey , 2013 .
[13] António E. Ruano,et al. The IMBPC HVAC system: A complete MBPC solution for existing HVAC systems , 2016 .
[14] Kamin Whitehouse,et al. The smart thermostat: using occupancy sensors to save energy in homes , 2010, SenSys '10.
[15] Frauke Oldewurtel,et al. Experimental analysis of model predictive control for an energy efficient building heating system , 2011 .
[16] David Barber,et al. Bayesian reasoning and machine learning , 2012 .
[17] Zhenjun Ma,et al. Supervisory and Optimal Control of Building HVAC Systems: A Review , 2008 .
[18] O. T. Masoso,et al. The dark side of occupants’ behaviour on building energy use , 2010 .
[19] Tianzhen Hong,et al. Occupancy schedules learning process through a data mining framework , 2015 .
[20] Geoffrey Qiping Shen,et al. Occupancy data analytics and prediction: A case study , 2016 .
[21] Arno Schlueter,et al. 3for2: Realizing spatial, material, and energy savings through integrated design , 2016 .
[22] Siaw Kiang Chou,et al. Achieving better energy-efficient air conditioning - A review of technologies and strategies , 2013 .
[23] Adrian Leaman,et al. Assessing building performance in use 3: energy performance of the Probe buildings , 2001 .
[24] Thomas Weng,et al. Occupancy-driven energy management for smart building automation , 2010, BuildSys '10.
[25] Philip S. Yu,et al. Top 10 algorithms in data mining , 2007, Knowledge and Information Systems.
[26] Peter Harrington,et al. Machine Learning in Action , 2012 .