An online learning approach for quantifying personalized thermal comfort via adaptive stochastic modeling

Building and Environment

Volumn 92, Issue , 2015, Pages 86-96

  Ghahramani, Ali ^a   Tang, Chao ^a   Becerik Gerber, Burcin ^a  

^a Univ of Southern California ^*  (United States)

Author keywords

Adaptive stochastic modeling; Commercial buildings; Online learning; Personalized comfort; Probabilistic modeling; Thermal comfort

Indexed keywords

BAYESIAN NETWORKS; COMPUTATIONAL COMPLEXITY; E-LEARNING; LEARNING SYSTEMS; OFFICE BUILDINGS; PARETO PRINCIPLE; STOCHASTIC SYSTEMS; THERMAL COMFORT;

BAYESIAN OPTIMAL CLASSIFIERS; COMMERCIAL BUILDING; ENVIRONMENTAL CONDITIONS; JOINT PROBABILITY DISTRIBUTIONS; KOLMOGOROV-SMIRNOV TEST; ONLINE LEARNING; PERSONALIZED COMFORT; PROBABILISTIC MODELING;

HVAC;

BAYESIAN ANALYSIS; BUILDING; INTERNET; LEARNING; MODELING; PROBABILITY; STOCHASTICITY;

UNITED STATES;

EID: 84929455875     PISSN: 03601323     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.buildenv.2015.04.017     Document Type: Article

References (44)

1. B.E.D. Book 2010, vol. 2011. US Department of Energy.
2. U.S.Energy Information Administration Emissions of greenhouse gases in the United States 2009, distribution of total U.S. greenhouse gas emissions by end-use sector 2011, Table3. DOE/EIA-0573(2009).
3. A.Standard, Standard 55-2004 Thermal environmental conditions for human occupancy 2004.
4. A.Standard, Standard 62.1-2010 Ventilation for acceptable indoor air quality 2010, American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc, Atlanta, GA.
5. Guan Y., Hosni M., Jones B., Gielda T. Literature review of the advances in thermal comfort modeling. Trans Am Soc Heat Refrig Air Cond Eng 2003, 109:908-916.
6. Jendritzky G., de Dear R. Adaptation and thermal environment. Biometeorology for adaptation to climate variability and change 2009,9-32. Springer.
7. Brager G.S., de Dear R.J. Thermal adaptation in the built environment: a literature review. Energy Build 1998, 27:83-96.
8. Nicol J.F., Humphreys M.A. Adaptive thermal comfort and sustainable thermal standards for buildings. Energy Build 2002, 34:563-572.
9. Cui W., Cao G., Park J.H., Ouyang Q., Zhu Y. Influence of indoor air temperature on human thermal comfort, motivation and performance. Build Environ 2013, 68:114-122.
10. Frontczak M., Wargocki P. Literature survey on how different factors influence human comfort in indoor environments. Build Environ 2011, 46:922-937.
11. Working Group III Mitigation of climate change, climate change 2014 2014, Mitigation of Climate Change, [Chapter 9].
12. Takada S., Matsumoto S., Matsushita T. Prediction of whole-body thermal sensation in the non-steady state based on skin temperature. Build Environ 2013, 68:123-133.
13. Choi J., Loftness V. Investigation of human body skin temperatures as a bio-signal to indicate overall thermal sensations. Build Environ 2012, 58:258-269.
14. Huizenga C., Zhang H., Arens E., Wang D. Skin and core temperature response to partial-and whole-body heating and cooling. JTherm Biol 2004, 29:549-558.
15. Choi J., Loftness V., Lee D. Investigation of the possibility of the use of heart rate as a human factor for thermal sensation models. Build Environ 2012, 50:165-175.
16. Bicego K.C., Barros R.C., Branco L.G. Physiology of temperature regulation: comparative aspects. Comp Biochem Physiol Part A: Mol Integr Physiol 2007, 147:616-639.
17. Auliciems A., Szokolay S.V. Thermal comfort 1997.
18. Huizenga C., Hui Z., Arens E. Amodel of human physiology and comfort for assessing complex thermal environments. Build Environ 2001, 36:691-699.
19. Russell S., Norvig P. A.Intelligence, a modern approach, artificial intelligence 1995, vol. 25. Prentice-Hall, Egnlewood Cliffs.
20. Fanger P.O. Thermal comfort. Analysis and applications in environmental engineering 1970, Thermal comfort. Analysis and applications in environmental engineering.
21. De Dear R., Brager G.S. Developing an adaptive model of thermal comfort and preference 1998, Center for the Built Environment.
22. Jazizadeh F., Marin F.M., Becerik-Gerber B. Athermal preference scale for personalized comfort profile identification via participatory sensing. Build Environ 2013, 68:140-149.
23. Bedford T. The warmth factor in comfort at work. A physiological study of heating and ventilation 1936, Industrial Health Research Board Report, Medical Research Council.
24. Zhang Y., Zhao R. Overall thermal sensation, acceptability and comfort. Build Environ 2008, 43:44-50.
25. Jazizadeh F., Ghahramani A., Becerik-Gerber B., Kichkaylo T., Orosz M. Ahuman-building interaction framework for personalized thermal comfort driven systems in office buildings. JComput Civ Eng 2013, 28(1):2-16.
26. Griffiths I., Boyce P. Performance and thermal comfort. Ergonomics 1971, 14:457-468.
27. Hardy J.D. Physiology of temperature regulation. Physiol Rev 1961, 41:221.
28. Zhao Q., Zhao Y., Wang F., Wang J., Jiang Y., Zhang F. Adata-driven method to describe the personalized dynamic thermal comfort in ordinary office environment: from model to application. Build Environ 2014, 72:309-318.
29. Liu W., Lian Z., Zhao B. Aneural network evaluation model for individual thermal comfort. Energy Build 2007, 39:1115-1122.
30. Simone A., Kolarik J., Iwamatsu T., Asada H., Dovjak M., Schellen L., et al. Arelation between calculated human body exergy consumption rate and subjectively assessed thermal sensation. Energy Build 2011, 43:1-9.
31. Yao R., Li B., Liu J. Atheoretical adaptive model of thermal comfort-adaptive predicted mean vote (aPMV). Build Environ 2009, 44:2089-2096.
32. Bermejo P., Redondo L., Ossa D.L., Rodriguez D., Flores J., Urea C., et al. Design and simulation of a thermal comfort adaptive system based on fuzzy logic and on-line learning. Energy Build 2012, 49:367-379.
33. Jazizadeh F, Ghahramani A, Becerik-Gerber B, Kichkaylo T, Orosz M. Personalized thermal comfort driven control in HVAC operated office buildings.
34. Friedman N., Geiger D., Goldszmidt M. Bayesian network classifiers. Mach Learn 1997, 29:131-163.
35. Murphy K.P. Machine learning: a probabilistic perspective 2012, MIT press.
36. James F. Statistical methods in experimental physics 2006, World Scientific Singapore.
37. Peel M.C., Finlayson B.L., McMahon T.A. Updated world map of the Köppen-Geiger climate classification. Hydrol Earth Syst Sci Discuss 2007, 4:439-473.
38. Dallman P.R. Plant life in the world's Mediterranean climates: California, Chile, South Africa, Australia, and the Mediterranean basin 1998, Univ of California Press.
39. Yang Z., Li N., Becerik-Gerber B., Orosz M. Asystematic approach to occupancy modeling in ambient sensor-rich buildings. Simulation 2014, 90:960-977.
40. Karjalainen S. Gender differences in thermal comfort and use of thermostats in everyday thermal environments. Build Environ 2007, 42:1594-1603.
41. Karyono T.H. Report on thermal comfort and building energy studies in Jakarta-Indonesia. Build Environ 2000, 35:77-90.
42. Karjalainen S. Thermal comfort and gender: a literature review. Indoor air 2012, 22:96-109.
43. Spagnolo J., De Dear R. Afield study of thermal comfort in outdoor and semi-outdoor environments in subtropical Sydney Australia. Build Environ 2003, 38:721-738.
44. Ghahramani A., Jazizadeh F., Becerik-Gerber B. Aknowledge based approach for selecting energy-aware and comfort-driven HVAC temperature set points. Energy Build 2014, 85:536-548.