X.Liang et al.Building and Environment 102(2016)179-192 185 Table 1 Table 2 The profile of Building 101. The data format of sensor records Location Philadelphia,U.S. Time step Sensor1 Sensor2 Sensor3 Sensor4 Size 6410m In Out Out n Out In Out Floor 3 floors Constructed Year 1911 1/120140:00 N11 N12 N13 N14 Nis N16 N17 N18 1/120140:05 Building Usage Office … 1/1/20140:10 e。 4e= =+ e+4 ”” 12/31201423:50 the i-th time step can be calculated by Eq.(6). 12/31201423:55 Nit Na Ni4 Nis Ncotal =>(Ni1 -Ni2+Ni3 -Ni4+Nis-Ng6+N:7-Nigs)(6) Weekday 200+ 180 3.Results e 3.1.General characteristics of occupant presence 碧140 120 This study uses the data from the year 2014 and the time step is 100 5 min.Due to the sensor failure and other reasons,there are some missing data,which is less than 1%of all samples.Based on the measured data of Building 101,general characteristics of the occupant presence were analyzed and compared among different 40 conditions based on statistical method. 20 The daily 24-h profile of occupant presence is the main target of this study.First,the hourly occupant presence of weekday and 234567891011121314151617181920212223 weekend is shown in Fig.7.The results show that the mean of Time occupant number is close to zero in the building during weekends Weekend and holidays and the variance is also low.It means there are nor- 200 mally few occupants in weekend and holiday.Therefore,when 180 analyzing the occupancy schedule,this study excludes the data from weekend and holidays.In weekdays,the mean of occupant number is significantly changed over time.The variation range of 140 occupant number is very large from 7 am to 4 pm in weekdays. 120 which exceeds more than 30%of the mean.It indicates the main 100 characteristics of occupant presence,dynamic,stochastic and highly variable.These characteristics lead to difficulty to under- stand and predict occupant presence based on traditional statistical 60 methods. Statistical results of hourly occupant presence from Monday to Friday are compared in Fig.8.It shows the features ofeach weekday 小+挂鞋主主挂中 are different.For example,the variance range at 11 am is much 0 1234567891011121314151617181920212223 smaller on Tuesday and Thursday than Monday and Wednesday. Time The particular values(extremely high values)on Friday are signif- Fig.7.Hourly occupant presence during weekdays and weekends. icantly lower than that of the other four days.Although the ● Sensors Unused Doors Occasional Door First Floor Fig.6.Sensor locations in Building 101.the i-th time step can be calculated by Eq. (6). Ntotal ¼ Xi 1ðNi1 Ni2 þ Ni3 Ni4 þ Ni5 Ni6 þ Ni7 Ni8Þ (6) 3. Results 3.1. General characteristics of occupant presence This study uses the data from the year 2014 and the time step is 5 min. Due to the sensor failure and other reasons, there are some missing data, which is less than 1% of all samples. Based on the measured data of Building 101, general characteristics of the occupant presence were analyzed and compared among different conditions based on statistical method. The daily 24-h profile of occupant presence is the main target of this study. First, the hourly occupant presence of weekday and weekend is shown in Fig. 7. The results show that the mean of occupant number is close to zero in the building during weekends and holidays and the variance is also low. It means there are nor￾mally few occupants in weekend and holiday. Therefore, when analyzing the occupancy schedule, this study excludes the data from weekend and holidays. In weekdays, the mean of occupant number is significantly changed over time. The variation range of occupant number is very large from 7 am to 4 pm in weekdays, which exceeds more than 30% of the mean. It indicates the main characteristics of occupant presence, dynamic, stochastic and highly variable. These characteristics lead to difficulty to under￾stand and predict occupant presence based on traditional statistical methods. Statistical results of hourly occupant presence from Monday to Friday are compared in Fig. 8. It shows the features of each weekday are different. For example, the variance range at 11 am is much smaller on Tuesday and Thursday than Monday and Wednesday. The particular values (extremely high values) on Friday are signif￾icantly lower than that of the other four days. Although the Table 1 The profile of Building 101. Location Philadelphia, U.S. Size 6410 m2 Floor 3 floors Constructed Year 1911 Building Usage Office Fig. 6. Sensor locations in Building 101. Table 2 The data format of sensor records. Time step Sensor1 Sensor2 Sensor3 Sensor4 In Out In Out In Out In Out 1/1/2014 0:00 N11 N12 N13 N14 N15 N16 N17 N18 1/1/2014 0:05 …. …. …. …. …. …. …. …. 1/1/2014 0:10 …. …. …. …. …. …. …. …. …. …. …. …. …. …. …. …. …. 12/31/2014 23:50 …. …. …. …. …. …. …. …. 12/31/2014 23:55 Ni1 Ni2 Ni3 Ni4 Ni5 Ni6 Ni7 Ni8 Fig. 7. Hourly occupant presence during weekdays and weekends. X. Liang et al. / Building and Environment 102 (2016) 179e192 185