A data-driven approach for window opening predictions in non-air-conditioned buildings

References

• Andersen, Rune Vinther, Jørn Toftum, Klaus Kaae Andersen, and Bjarne W. Olesen. 2009. “Survey of Occupant Behaviour and Control of Indoor Environment in Danish Dwellings.” Energy and Buildings 41 (1): 11–16. doi:10.1016/j.enbuild.2008.07.004.
   Web of Science ®Google Scholar
• ASHRAE. 2017. ANSI/ASHRAE Standard 55-2017 : Thermal Environmental Conditions for Human Occupancy. ASHRAE Inc.
   Google Scholar
• Brager, Gail, Gwelen Paliaga, and Richard de Dear. 2004. “Operable Windows, Personal Control,and Occupant Comfort.” ASHRAE Transactions 110: Part 2. https://escholarship.org/uc/item/4x57v1pf.
   Google Scholar
• Conceição, Eusébio Z. E., João M. M. Gomes, Nuno H. Antão, and Ma Manuela J. R. Lúcio. 2012. “Application of a Developed Adaptive Model in the Evaluation of Thermal Comfort in Ventilated Kindergarten Occupied Spaces.” Building and Environment 50: 190–201. doi:10.1016/j.buildenv.2011.10.013.
   Web of Science ®Google Scholar
• Costanzo, Vincenzo, Runming Yao, Tiantian Xu, Jie Xiong, Qiulei Zhang, and Baizhan Li. 2019. “Natural Ventilation Potential for Residential Buildings in a Densely Built-up and Highly Polluted Environment. A Case Study.” Renewable Energy 138: 340–353. doi:10.1016/j.renene.2019.01.111.
   Web of Science ®Google Scholar
• Deng, Zhipeng, and Qingyan Chen. 2018. “Artificial Neural Network Models Using Thermal Sensations and Occupants’ Behavior for Predicting Thermal Comfort.” Energy and Buildings 174: 587–602. doi:10.1016/j.enbuild.2018.06.060.
   Web of Science ®Google Scholar
• Deuble, Max Paul, and Richard John de Dear. 2014. “Is It Hot in Here or Is It Just Me? Validating the Post-Occupancy Evaluation.” Intelligent Buildings International. doi:10.1080/17508975.2014.883299.
   Google Scholar
• D’Oca, Simona, and Tianzhen Hong. 2014. “A Data-Mining Approach to Discover Patterns of Window Opening and Closing Behavior in Offices.” Building and Environment 82: 726–739. doi:10.1016/j.buildenv.2014.10.021.
   Web of Science ®Google Scholar
• Dutton, Spencer, and Li Shao. 2010. “Window Opening Behaviour in a Naturally Ventilated School.” Proceedings of SimBuild 4 (1): 260–268.
   Google Scholar
• Fabi, Valentina, Rune Vinther Andersen, Stefano Corgnati, and Bjarne W Olesen. 2012. “Occupants’ Window Opening Behaviour: A Literature Review of Factors Influencing Occupant Behaviour and Models.” Building and Environment 58: 188–198. doi:10.1016/j.buildenv.2012.07.009.
   Web of Science ®Google Scholar
• Friedman, Jerome H. 2001. “Greedy Function Approximation: A Gradient Boosting Machine.” The Annals of Statistics 29 (5): 1189–1536. http://www.jstor.org/stable/2699986.
   Web of Science ®Google Scholar
• Grabe, Jörn von. 2016. “Potential of Artificial Neural Networks to Predict Thermal Sensation Votes.” Applied Energy 161: 412–424. doi:10.1016/j.apenergy.2015.10.061.
   Web of Science ®Google Scholar
• Haldi, Frédéric, and Darren Robinson. 2009. “Interactions with Window Openings by Office Occupants.” Building and Environment 44 (12): 2378–2395. doi:10.1016/j.buildenv.2009.03.025.
   Web of Science ®Google Scholar
• Han, Jiawei, Micheline Kamber, and Jian Pei. 2006. Data Mining: Concepts and Techniques. 2nd Edition. San Francisco: Morgan Kaufmann Publishers.
   Google Scholar
• Herkel, Sebastian, Ulla Knapp, and Jens Pfafferott. 2008. “Towards a Model of User Behaviour Regarding the Manual Control of Windows in Office Buildings.” Building and Environment 43 (4): 588–600. doi:10.1016/j.buildenv.2006.06.031.
   Web of Science ®Google Scholar
• Hoof, J. Van. 2008. “Forty Years of Fanger’s Model of Thermal Comfort: Comfort for All?” Indoor Air 18 (3): 182–201. doi:10.1111/j.1600-0668.2007.00516.x.
   PubMed Web of Science ®Google Scholar
• Khayatian, Fazel, Luca Sarto, and Giuliano Dall’O’. 2016. “Application of Neural Networks for Evaluating Energy Performance Certificates of Residential Buildings.” Energy and Buildings 125: 45–54. doi:10.1016/j.enbuild.2016.04.067.
   Web of Science ®Google Scholar
• Kim, Jeong Tai, Ji Hyun Lim, Sun Ho Cho, and Geun Young Yun. 2015. “Development of the Adaptive PMV Model for Improving Prediction Performances.” Energy and Buildings 98: 100–105. doi:10.1016/j.enbuild.2014.08.051.
   Web of Science ®Google Scholar
• Kohavi, Ron. 1995. “A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection.” International Joint Conference of Artificial Intelligence.
   Google Scholar
• Li, Nan, Juncheng Li, Ruijuan Fan, and Hongyuan Jia. 2015. “Probability of Occupant Operation of Windows during Transition Seasons in Office Buildings.” Renewable Energy 73: 84–91. doi:10.1016/j.renene.2014.05.065.
   Web of Science ®Google Scholar
• Manu, Sanyogita, Yash Shukla, Rajan Rawal, Leena E. Thomas, and Richard de Dear. 2016. “Field Studies of Thermal Comfort across Multiple Climate Zones for the Subcontinent: India Model for Adaptive Comfort (IMAC).” Building and Environment 98: 55–70. doi:10.1016/j.buildenv.2015.12.019.
   Web of Science ®Google Scholar
• Markovic, Romana, Eva Grintal, Daniel Wölki, Jérôme Frisch, and Christoph van Treeck. 2018. “Window Opening Model Using Deep Learning Methods.” Building and Environment 145: 319–329. doi:10.1016/j.buildenv.2018.09.024.
   Web of Science ®Google Scholar
• Nicol, J. Fergus, and Humphreys Michael. 2004. “A Stochastic Approach to Thermal Comfort-Occupant Behavior and Energy Use in Buildings.” ASHRAE Transactions 110: 554–568.
   Google Scholar
• Pan, Song, Yingzi Xiong, Yiye Han, Xingxing Zhang, Liang Xia, Shen Wei, Jinshun Wu, and Mengjie Han. 2018. “A Study on Influential Factors of Occupant Window-Opening Behavior in an Office Building in China.” Building and Environment 133: 41–50. doi:10.1016/j.buildenv.2018.02.008.
   Web of Science ®Google Scholar
• Quinlan, J. R. 1986. “Induction of Decision Trees.” Machine Learning 1 (1): 81–106. doi:10.1007/bf00116251.
   Google Scholar
• Raja, Iftikhar A, J. F. Nicol, and K. J. McCartney. 1998. “Natural Ventilated Buildings: Use of Controls for Changing Indoor Climate.” Renewable Energy 15 (1): 391–394. doi:10.1016/S0960-1481(98)00193-1.
   Web of Science ®Google Scholar
• Schakib-Ekbatan, Karin, Fatma Zehra Çakıcı, Marcel Schweiker, and Andreas Wagner. 2015. “Does the Occupant Behavior Match the Energy Concept of the Building? – Analysis of a German Naturally Ventilated Office Building.” Building and Environment 84: 142–150. doi:10.1016/j.buildenv.2014.10.018.
   Web of Science ®Google Scholar
• Shi, Zhenni, Hua Qian, Xiaohong Zheng, Zhengfei Lv, Yuguo Li, Li Liu, and Peter V. Nielsen. 2018. “Seasonal Variation of Window Opening Behaviors in Two Naturally Ventilated Hospital Wards.” Building and Environment 130: 85–93. doi:10.1016/j.buildenv.2017.12.019.
   PubMed Web of Science ®Google Scholar
• Takasu, Marina, Ryozo Ooka, Hom B. Rijal, Madhavi Indraganti, and Manoj Kumar Singh. 2017. “Study on Adaptive Thermal Comfort in Japanese Offices under Various Operation Modes.” Building and Environment 118: 273–288. doi:10.1016/j.buildenv.2017.02.023.
   Web of Science ®Google Scholar
• Vallianos, Charalampos, Andreas Athienitis, and Jiwu Rao. 2019. “Hybrid Ventilation in an Institutional Building: Modeling and Predictive Control.” Building and Environment 166: 106405. doi:10.1016/j.buildenv.2019.106405.
   Web of Science ®Google Scholar
• Wang, Zhe, Richard de Dear, Maohui Luo, Borong Lin, Yingdong He, Ali Ghahramani, and Yingxin Zhu. 2018. “Individual Difference in Thermal Comfort: A Literature Review.” Building and Environment 138: 181–193. doi:10.1016/j.buildenv.2018.04.040.
   Web of Science ®Google Scholar
• Wei, Shen, Tarek M. Hassan, Steven K. Firth, and Farid Fouchal. 2017. “Impact of Occupant Behaviour on the Energy-Saving Potential of Retrofit Measures for a Public Building in the UK.” Intelligent Buildings International. doi:10.1080/17508975.2016.1139538.
   Web of Science ®Google Scholar
• Wu, Zhibin, Nianping Li, Jinqing Peng, Haijiao Cui, Penglong Liu, Hongqiang Li, and Xiwang Li. 2018. “Using an Ensemble Machine Learning Methodology-Bagging to Predict Occupants’ Thermal Comfort in Buildings.” Energy and Buildings 173: 117–127. doi:10.1016/j.enbuild.2018.05.031.
   Web of Science ®Google Scholar
• Yao, Runming, Baizhan Li, and Jing Liu. 2009. “A Theoretical Adaptive Model of Thermal Comfort – Adaptive Predicted Mean Vote (aPMV).” Building and Environment 44 (10): 2089–2096. doi:10.1016/j.buildenv.2009.02.014.
   Web of Science ®Google Scholar
• Yun, Geun Young, and Koen Steemers. 2008. “Time-Dependent Occupant Behaviour Models of Window Control in Summer.” Building and Environment 43 (9): 1471–1482. doi:10.1016/j.buildenv.2007.08.001.
   Web of Science ®Google Scholar
• Zhang, Yufan, and Peter Barrett. 2012. “Factors Influencing the Occupants’ Window Opening Behaviour in a Naturally Ventilated Office Building.” Building and Environment 50: 125–134. doi:10.1016/j.buildenv.2011.10.018.
   Web of Science ®Google Scholar
• Zhao, Rongyi, Shufeng Sun, and Rongyi Ding. 2004. “Conditioning Strategies of Indoor Thermal Environment in Warm Climates.” Energy and Buildings 36 (12): 1281–1286. doi:10.1016/j.enbuild.2003.07.002.
   Web of Science ®Google Scholar
• Zhou, Xin, Tiance Liu, Xing Shi, and Xing Jin. 2018. “Case Study of Window Operating Behavior Patterns in an Open-Plan Office in the Summer.” Energy and Buildings 165: 15–24. doi:10.1016/j.enbuild.2018.01.037.
   Web of Science ®Google Scholar