An improved window opening behavior model involving the division of the dummy variable’s interval level: Case study of an office building in Xi’an during summer

Window opening behavior significantly impacts indoor air quality, thermal comfort, and energy consumption. A field measurement was carried out in three typical rooms (a standard office, a meeting room and a smoking office) within an office building. The window state and the physical environment were continuously recorded during the measured periods. Three typical window opening behaviors were found in the measured samples, namely, active, moderate, and passive. The common logistic regression coefficient indicated that solar radiation exhibited the greatest effect on window opening behavior in the smoking office and standard office. Typically, window opening behavior in the meeting room was the most strongly correlated with time of the day, mainly because of the meeting schedule for occupants in the meeting room. This study discussed the dividing principles involved in setting the dummy variable interval level (discretizing continuous variables and dividing them into different intervals), and proposed a method to determine the optimal interval level of each variable. The improved model led to the increase in the prediction accuracy rate of the window being opened by 2.0% and 3.3% according to the comparison with the original model based on dummy variables and the common model based on continuous variables, respectively. This study can provide a reference value for simulating energy consumption in office buildings in the future.