Learning occupants’ indoor comfort temperature through a Bayesian inference approach for office buildings in United States
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Zhe Wang | Tianzhen Hong | T. Hong | Zhe Wang
[1] Tord Kjellstrom,et al. Workplace heat stress, health and productivity – an increasing challenge for low and middle-income countries during climate change , 2009, Global health action.
[2] Athanasios Tzempelikos,et al. Inference of thermal preference profiles for personalized thermal environments with actual building occupants , 2019, Building and Environment.
[3] Wouter D. van Marken Lichtenbelt,et al. Energy consumption in buildings and female thermal demand , 2015 .
[4] Richard de Dear,et al. Individual difference in thermal comfort: A literature review , 2018, Building and Environment.
[5] Xiao Chen,et al. Occupant feedback based model predictive control for thermal comfort and energy optimization: A chamber experimental evaluation , 2016 .
[6] Qinglin Meng,et al. Thermal comfort in buildings with split air-conditioners in hot-humid area of China , 2013 .
[7] Shinichi Tanabe,et al. Effect of humidity on human comfort and productivity after step changes from warm and humid environment , 2007 .
[8] Gail Brager,et al. A Comparison of Methods for Assessing Thermal Sensation and Acceptability in the Field , 1993 .
[9] Nan Li,et al. Linking energy-cyber-physical systems with occupancy prediction and interpretation through WiFi probe-based ensemble classification , 2019, Applied Energy.
[10] John K Kruschke,et al. Bayesian data analysis. , 2010, Wiley interdisciplinary reviews. Cognitive science.
[11] Liu Yang,et al. Thermal comfort and building energy consumption implications - A review , 2014 .
[12] Hui Zhang,et al. EXTENDING AIR TEMPERATURE SETPOINTS: SIMULATED ENERGY SAVINGS AND DESIGN CONSIDERATIONS FOR NEW AND RETROFIT BUILDINGS , 2015 .
[13] Mohammad. Rasul,et al. Thermal-comfort analysis and simulation for various low-energy cooling-technologies applied to an office building in a subtropical climate , 2008 .
[14] Jan Hensen,et al. Thermal comfort in residential buildings: Comfort values and scales for building energy simulation , 2009 .
[15] Xiao Chen,et al. A data-driven state-space model of indoor thermal sensation using occupant feedback for low-energy buildings , 2015 .
[16] Ryozo Ooka,et al. Adaptive model of thermal comfort for offices in hot and humid climates of India , 2014 .
[17] Yi Jiang,et al. Review of thermal comfort infused with the latest big data and modeling progresses in public health , 2019, Building and Environment.
[18] Athanasios Tzempelikos,et al. Bayesian classification and inference of occupant visual preferences in daylit perimeter private offices , 2018 .
[19] Ilias Bilionis,et al. A Bayesian modeling approach of human interactions with shading and electric lighting systems in private offices , 2017 .
[20] Gail Brager,et al. Thermal comfort in naturally ventilated buildings: revisions to ASHRAE Standard 55 , 2002 .
[21] Min Li,et al. Can personal control influence human thermal comfort? A field study in residential buildings in China in winter , 2014 .
[22] M. Tribus,et al. Probability theory: the logic of science , 2003 .
[23] S. Tanabe,et al. Thermal comfort and productivity in offices under mandatory electricity savings after the Great East Japan earthquake , 2012 .
[24] Junta Nakano,et al. Differences in perception of indoor environment between Japanese and non-Japanese workers , 2002 .
[25] Hyojin Kim,et al. Development of the ASHRAE Global Thermal Comfort Database II , 2018, Building and Environment.
[26] Bing Dong,et al. Occupancy behavior based model predictive control for building indoor climate—A critical review , 2016 .
[27] Sivakumar Kumaresan,et al. Field study of thermal comfort in residential buildings in the equatorial hot-humid climate of Malaysia , 2013 .
[28] E. Halawa,et al. The adaptive approach to thermal comfort: A critical overview , 2012 .
[29] 新 雅夫,et al. ASHRAE(American Society of Heating,Refrigerating and Air-Conditioning Engineers)大会"国際年"行事に参加して , 1975 .
[30] Jelena Srebric,et al. Impact of occupancy rates on the building electricity consumption in commercial buildings , 2017 .
[31] Athanasios Tzempelikos,et al. A Bayesian approach for probabilistic classification and inference of occupant thermal preferences in office buildings , 2017 .
[32] Q. Ouyang,et al. Field study of human thermal comfort and thermal adaptability during the summer and winter in Beijing , 2011 .
[33] Nicolas Morel,et al. Bayesian estimation of visual discomfort , 2008 .
[34] Saman Rashidi,et al. Porous materials in building energy technologies—A review of the applications, modelling and experiments , 2018, Renewable and Sustainable Energy Reviews.
[35] Marcel Schweiker,et al. Thermo-specific self-efficacy (specSE) in relation to perceived comfort and control , 2016 .
[36] J. Alves e Sousa,et al. Uncertainty Analysis of Thermal Comfort Parameters , 2015 .
[37] Q. Ouyang,et al. Investigation of indoor environment quality of Chinese large-hub airport terminal buildings through longitudinal field measurement and subjective survey , 2015 .
[38] Baizhan Li,et al. Occupants' adaptive responses and perception of thermal environment in naturally conditioned university classrooms , 2010 .
[39] Ö. Boydak,et al. Commercial Buildings Energy Consumption Survey (CBECS) and Its Comparison with Turkey Applications , 2017 .
[40] D. Bluma,et al. Practical Factors of Envelope Model Setup and Their Effects on the Performance of Model Predictive Control for Building Heating, Ventilating, and Air Conditioning Systems , 2019 .
[41] P. O. Fanger,et al. Thermal comfort: analysis and applications in environmental engineering, , 1972 .
[42] Maohui Luo,et al. The dynamics of thermal comfort expectations: The problem, challenge and impication , 2016 .
[43] Sami Karjalainen,et al. Thermal comfort and use of thermostats in Finnish homes and offices , 2009 .
[44] Zhongbing Liu,et al. Review of energy conservation technologies for fresh air supply in zero energy buildings , 2019, Applied Thermal Engineering.
[45] Joyce Kim,et al. Personal comfort models – A new paradigm in thermal comfort for occupant-centric environmental control , 2018 .
[46] Hiroshi Tsuji,et al. Bayesian networks for thermal comfort analysis , 2007, 2007 IEEE International Conference on Systems, Man and Cybernetics.
[47] M Frontczak,et al. Quantitative relationships between occupant satisfaction and satisfaction aspects of indoor environmental quality and building design. , 2012, Indoor air.
[48] Yingxin Zhu,et al. Exploring the dynamic process of human thermal adaptation: A study in teaching building , 2016 .
[49] Michael A. Humphreys,et al. ADAPTIVE THERMAL COMFORT AND SUSTAINABLE THERMAL STANDARDS FOR BUILDINGS , 2002 .
[50] Na Zhu,et al. Occupancy prediction through Markov based feedback recurrent neural network (M-FRNN) algorithm with WiFi probe technology , 2018, Building and Environment.
[51] S. Karjalainen,et al. Thermal comfort and gender: a literature review. , 2012, Indoor air.
[52] Richard de Dear,et al. Rational selection of heating temperature set points for China's hot summer – Cold winter climatic region , 2015 .
[53] Gail Brager,et al. Developing an adaptive model of thermal comfort and preference , 1998 .
[54] Jin Wen,et al. Modeling thermal comfort holistically: Bayesian estimation of thermal sensation, acceptability, and preference distributions for office building occupants , 2013 .
[55] K. Steemers,et al. Household energy consumption: a study of the role of occupants , 2009 .
[56] J. van Hoof. Forty years of Fanger's model of thermal comfort: comfort for all? , 2008, Indoor air.
[57] Li Lan,et al. The effects of air temperature on office workers' well-being, workload and productivity-evaluated with subjective ratings. , 2010, Applied ergonomics.