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Published in:
2020 | OriginalPaper | Chapter
Research on Behavior Pattern Prediction at Early Stage of Design
Authors : Panyu Zhu, Da Yan, Hongsan Sun, Chenxi Gui
Published in: Proceedings of the 11th International Symposium on Heating, Ventilation and Air Conditioning (ISHVAC 2019)
Publisher: Springer Singapore
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Abstract
Occupant behavior has great impact on building energy consumption. Lots of efforts have been contributed to bridging the gap between simulated energy performance and the reality. Nevertheless, the prediction of potential behavior pattern in a to-be-built building is lack of researches. This study presented an approach to predict the probability of certain behavior pattern basing on available inputs at design stage. Five hundred and forty-six questionnaires about energy-related behavior preference were collected by online survey, from which the control pattern of air conditioner was analyzed and used as data source of this research. A feed forward neural network model with two hidden layers was built and trained to calculate the probability of certain behavior pattern, where the pattern “turning on air conditioner when feel hot” was taken as an example. As result of this research, the trained ANN model was cross-tested by 100 randomly selected “testing group” and reported average correct rate of 61%.