Abdi H, Williams LJ (2010). Newman-Keuls test and Tukey test. In: Salkind NJ (ed), Encyclopedia of Research Design. Thousand Oaks, CA, UAA: Sage.
Aguilera JJ, Kazanci OB, Toftum J (2019). Thermal adaptation in occupant-driven HVAC control. Journal of Building Engineering, 25: 100846.
Antoniadou P, Papadopoulos AM (2017). Occupants’ thermal comfort: State of the art and the prospects of personalized assessment in office buildings. Energy and Buildings, 153: 136–149.
ASHRAE (2017). ASHRAE Standard 55-2017: Thermal Environmental Conditions for Human Occupancy. Atlanta: American Society of Heating, Refrigerating and Air-Conditioning Engineers.
Buonocore C, de Vecchi R, Scalco V, et al. (2019). Influence of recent and long-term exposure to air-conditioned environments on thermal perception in naturally-ventilated classrooms. Building and Environment, 156: 233–242.
Cai J, Li B, Yu W, et al. (2020). Associations of household dampness with asthma, allergies, and airway diseases among preschoolers in two cross-sectional studies in Chongqing, China: Repeated surveys in 2010 and 2019. Environment International, 140: 105752.
Chaudhuri T, Zhai D, Soh YC, et al. (2018a). Random forest based thermal comfort prediction from gender-specific physiological parameters using wearable sensing technology. Energy and Buildings, 166: 391–406.
Chaudhuri T, Zhai D, Soh YC, et al. (2018b). Thermal comfort prediction using normalized skin temperature in a uniform built environment. Energy and Buildings, 159: 426–440.
Chaudhuri T, Soh YC, Li H, et al. (2020). Machine learning driven personal comfort prediction by wearable sensing of pulse rate and skin temperature. Building and Environment, 170: 106615.
China Meteorological Administration (2019). The Ground Climate Data of China. Available at http://data.cma.cn
Choi JH, Loftness V (2012). Investigation of human body skin temperatures as a bio-signal to indicate overall thermal sensations. Building and Environment, 58: 258–269.
Choi JH, Loftness V, Lee DW (2012). Investigation of the possibility of the use of heart rate as a human factor for thermal sensation models. Building and Environment, 50: 165–175.
Choi J-H, Yeom D (2017). Study of data-driven thermal sensation prediction model as a function of local body skin temperatures in a built environment. Building and Environment, 121: 130–147.
Cohen J (1988). Statistical Power Analysis for the Behavioral Sciences, 2nd edn. Mahwah, NJ, USA: Lawrence Erlbaum Associates Publisher.
Dai C, Zhang H, Arens E, et al. (2017). Machine learning approaches to predict thermal demands using skin temperatures: Steady-state conditions. Building and Environment, 114: 1–10.
Du C, Li B, Liu H, et al. (2019). Quantification of personal thermal comfort with localized airflow system based on sensitivity analysis and classification tree model. Energy and Buildings, 194: 1–11.
Fanger PO (1970). Thermal comfort. Analysis and applications in environmental engineering. Copenhagen: Danish Technical Press.
Fanger PO, Toftum J (2002). Extension of the PMV model to non-air-conditioned buildings in warm climates. Energy and Buildings, 34: 533–536.
Faul F, Erdfelder E, Lang AG, et al. (2007). G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39: 175–191.
Faul F, Erdfelder E, Buchner A, et al. (2009). Statistical power analyses using G*Power 3.1: Tests for correlation and regression analyses. Behavior Research Methods, 41: 1149–1160.
Gagge AP, Fobelets AP, Berglund LG (1986). Standard predictive index of human response to the thermal environment. ASHRAE Transactions, 92(2B): 709–731.
Gilani SI-u-H, Khan MH, Ali M (2016). Revisiting Fanger’s thermal comfort model using mean blood pressure as a bio-marker: an experimental investigation. Applied Thermal Engineering, 109: 35–43.
ISO (2002). ISO 10551:1995. Ergonomics of the thermal environment—Assessment of the influence of the thermal environment using subjective judgement scales.
ISO (2005). EN ISO 7730:2005, Ergonomics of the thermal environment—Analytical determination and interpretation of thermal comfort using calculation of the PMV and PPD indices and local thermal comfort criteria.
Jessen C (2012). Temperature Regulation In Humans And Other Mammals. Berlin: Springer.
Ji W, Cao B, Luo M, et al. (2017). Influence of short-term thermal experience on thermal comfort evaluations: a climate chamber experiment. Building and Environment, 114: 246–256.
Ji W, Cao B, Geng Y, et al. (2019). A study on the influences of immediate thermal history on current thermal sensation. Energy and Buildings, 198: 364–376.
Jowkar M, de Dear R, Brusey J (2020). Influence of long-term thermal history on thermal comfort and preference. Energy and Buildings, 210: 109685.
Kim J, Schiavon S, Brager G (2018). Personal comfort models — A new paradigm in thermal comfort for occupant-centric environmental control. Building and Environment, 132: 114–124.
Kong D, Liu H, Wu Y, et al. (2019). Effects of indoor humidity on building occupants’ thermal comfort and evidence in terms of climate adaptation. Building and Environment, 155: 298–307.
Lan L, Lian Z (2010). Application of statistical power analysis—How to determine the right sample size in human health, comfort and productivity research. Building and Environment, 45: 1202–1213.
Li B, Li W, Liu H, et al. (2010). Physiological expression of human thermal comfort to indoor operative temperature in the non-HVAC environment. Indoor and Built Environment, 19: 221–229.
Li B, Yao R (2012). Building energy efficiency for sustainable development in China: challenges and opportunities. Building Research & Information, 40: 417–431.
Li B, Du C, Yao R, et al. (2018a). Indoor thermal environments in Chinese residential buildings responding to the diversity of climates. Applied Thermal Engineering, 129: 693–708.
Li W, Zhang J, Zhao T, et al. (2018b). Experimental research of online monitoring and evaluation method of human thermal sensation in different active states based on wristband device. Energy and Buildings, 173: 613–622.
Liu W, Lian Z, Deng Q, et al. (2011). Evaluation of calculation methods of mean skin temperature for use in thermal comfort study. Building and Environment, 46: 478–488.
Liu H, Wu Y, Li B, et al. (2017a). Seasonal variation of thermal sensations in residential buildings in the Hot Summer and Cold Winter zone of China. Energy and Buildings, 140: 9–18.
Liu Y, Dong Y, Song C, et al. (2017b). A tracked field study of thermal adaptation during a short-term migration between cold and hot-summer and warm-winter areas of China. Building and Environment, 124: 90–103.
Liu H, Wu Y, Lei D, Li B (2018a). Gender differences in physiological and psychological responses to the thermal environment with varying clothing ensembles. Building and Environment, 141: 45–54.
Liu W, Yang D, Shen X, et al. (2018b). Indoor clothing insulation and thermal history: A clothing model based on logistic function and running mean outdoor temperature. Building and Environment, 135: 142–152.
Liu S, Schiavon S, Das HP, et al. (2019). Personal thermal comfort models with wearable sensors. Building and Environment, 162: 106281.
Liu Y, Dong Y, Song C, et al. (2020). Dynamic process of behavioral adaptation of migrants with different thermal experiences: A long-term follow-up field survey. Energy and Buildings, 207: 109605.
Luo M, de Dear R, Ji W, et al. (2016a). The dynamics of thermal comfort expectations: The problem, challenge and impication. Building and Environment, 95: 322–329.
Luo M, Ji W, Cao B, et al. (2016b). Indoor climate and thermal physiological adaptation: Evidences from migrants with different cold indoor exposures. Building and Environment, 98: 30–38.
Luo M, Wang Z, Brager G, et al. (2018). Indoor climate experience, migration, and thermal comfort expectation in buildings. Building and Environment, 141: 262–272.
Luo M, Ke Z, Ji W, et al. (2019). The time-scale of thermal comfort adaptation in heated and unheated buildings. Building and Environment, 151: 175–186.
McIntyre DA (1980). Indoor Climate. London: Applied Science Publishers.
McKemy DD (2005). How cold is it? TRPM8 and TRPA1 in the molecular logic of cold sensation. Molecular Pain, https://doi.org/10.1186/1744-8069-1-16.
MOHURD (2016). GB 50176. China National Standard: Thermal Design Code for the Civil Building. Beijing: Ministry of Housing and urban-Rural Development (MOHuRD). (in Chinese)
Nicol F, Humphreys M (2010). Derivation of the adaptive equations for thermal comfort in free-running buildings in European standard EN15251. Building and Environment, 45: 11–17.
Ning H, Wang Z, Ji Y (2016a). Thermal history and adaptation: Does a long-term indoor thermal exposure impact human thermal adaptability? Applied Energy, 183: 22–30.
Ning H, Wang Z, Zhang X, et al. (2016b). Adaptive thermal comfort in university dormitories in the severe cold area of China. Building and Environment, 99: 161–169.
Nkurikiyeyezu KN, Suzuki Y, Lopez GF (2018). Heart rate variability as a predictive biomarker of thermal comfort. Journal of Ambient Intelligence and Humanized Computing, 9: 1465–1477.
Onset (2019). HOBO, UX120-006M. Available at https://www.onsetcomp.com/
Pandya R, Pandya J (2015). C5.0 algorithm to improved decision tree with feature selection and reduced error pruning. International Journal of Computer Applications, 117: 18–21.
Pang S-l, Gong J-z (2009). C5.0 classification algorithm and application on individual credit evaluation of banks. Systems Engineering — Theory & Practice, 29: 94–104.
Parkinson T, de Dear R, Candido C (2016). Thermal pleasure in built environments: alliesthesia in different thermoregulatory zones. Building Research & Information, 44: 20–33.
Patil N, Lathi R, Chitre V (2012). Comparison of C5. 0 & CART classification algorithms using pruning technique. International Journal of Engineering Research & Technology, 1: 1–5.
Revel GM, Sabbatini E, Arnesano M (2012). Development and experimental evaluation of a thermography measurement system for real-time monitoring of comfort and heat rate exchange in the built environment. Measurement Science and Technology, 23: 035005.
Salehi B, Ghanbaran AH, Maerefat M (2020). Intelligent models to predict the indoor thermal sensation and thermal demand in steady state based on occupants’ skin temperature. Building and Environment, 169: 106579.
Sharma N, Mukherjee S (2012). A novel multi-classifier layered approach to improve minority attack detection in IDS. Procedia Technology, 6: 913–921.
Story GM, Peier AM, Reeve AJ, et al. (2003). ANKTM1, a TRP-like channel expressed in nociceptive neurons, is activated by cold temperatures. Cell, 112: 819–829.
WMA (2013). WMA Declaration of Helsinki — Ethical Principles for Medical Research Involving Human Subjects. World Medical Association.
Wu Y, Liu H, Li B, et al. (2018). Behavioural, physiological and psychological responses of passengers to the thermal environment of boarding a flight in winter. Ergonomics, 61: 796–805.
Wu Y, Liu H, Li B, et al. (2019a). Thermal adaptation of the elderly during summer in a hot humid area: Psychological, behavioral, and physiological responses. Energy and Buildings, 203: 109450.
Wu Y, Yuan M, Li C, et al. (2019b). The effect of indoor thermal history on human thermal responses in cold environments of early winter. Journal of Thermal Biology, 86: 102448.
Wu Z, Li N, Peng J, Li J (2019c). Effect of long-term indoor thermal history on human physiological and psychological responses: A pilot study in university dormitory buildings. Building and Environment, 166: 106425.
Wu Y, Liu H, Chen B, Li B, et al. (2020a). Effect of long-term thermal history on physiological acclimatization and prediction of thermal sensation in typical winter conditions. Building and Environment, 179: 106936.
Wu Y, Liu H, Li B, et al. (2020b). Evaluation and modification of the weighting formulas for mean skin temperature of human body in winter conditions. Energy and Buildings, 229: 110390.
Wu Y, Mäki A, Jokisalo J, et al. (2021). Demand response of district heating using model predictive control to prevent the draught risk of cold window in an office building. Journal of Building Engineering, 33: 101855.
Yan H, Liu Q, Zhang H, et al. (2019). Difference in the thermal response of the occupants living in northern and Southern China. Energy and Buildings, 204: 109475.
Yang B, Li X, Hou Y, et al. (2020). Non-invasive (non-contact) measurements of human thermal physiology signals and thermal comfort/discomfort poses — A review. Energy and Buildings, 224: 110261.
Yao R, Li B, Liu J (2009). A theoretical adaptive model of thermal comfort — Adaptive Predicted Mean Vote (aPMV). Building and Environment, 44: 2089–2096.
Yasmeen S, Liu H, Wu Y, et al. (2020). Physiological responses of acclimatized construction workers during different work patterns in a hot and humid subtropical area of China. Journal of Building Engineering, 30: 101281.
Yau YH, Chew BT (2014). A review on predicted mean vote and adaptive thermal comfort models. Building Services Engineering Research and Technology, 35: 23–35.
Yu W, Li B, Jia H, et al. (2015). Application of multi-objective genetic algorithm to optimize energy efficiency and thermal comfort in building design. Energy and Buildings, 88: 135–143.
Yuan X, Pan Y, Yang J, et al. (2021). Study on the application of reinforcement learning in the operation optimization of HVAC system. Building Simulation, 14: 75–87.
Zhang Y, Chen H, Wang J, et al. (2016). Thermal comfort of people in the hot and humid area of China—Impacts of season, climate, and thermal history. Indoor Air, 26: 820–830.
Zhang S, Cheng Y, Oladokun MO, et al. (2020). Improving predicted mean vote with inversely determined metabolic rate. Sustainable Cities and Society, 53: 101870.
Zhao Q, Lian Z, Lai D (2021). Thermal Comfort models and their developments: A review. Energy and Built Environment, 2: 21–33.
