A stochastic model of user behaviour regarding ventilation

Personal comfort models: Predicting individuals' thermal preference using occupant heating and cooling behavior and machine learning

“…Behavior literature [42][43][44][45][46] tends to focus on predicting the state of thermal control devices to estimate their effects on the indoor environment, without analyzing the impact on comfort. Conversely, comfort literature [14,15,36] generally focuses on assessing the thermal comfort of occupants who have access to those devices without explicitly accounting for their actual control actions.…”

Factors affecting ‘end-of-day’ window position in a non-air-conditioned office building

“…There is no distinction made between one office being occupied for 2 days and 2 offices being occupied for only one day; both would yield a sample-day count ( ' n ) of 2. The sample-day count has been used to calculate a value for φ , defined as the proportion of windows left open on departure, using, t , has been demonstrated to be a strong indicator of window operation in a number of studies [5][6][7][8][9][10] as well as this one, and so has been adopted here as the driving variable against which φ is plotted in all cases.…”

“…Therefore, environmental factors such as indoor air temperature [3,4] or outdoor air temperature [5][6][7][8] or a combination of them [9,10] were proposed to be the main 'driver(s) ' for occupants to open/close their windows. In addition, some non-environmental factors were also identified to have an influence on the window state, such as the previous window state [6,10,11], time of day [6,10,11], occupancy pattern [6,10], season [6], floor level [10], personal difference [4,9,10] and building orientation [7].…”

Retrofit Planning for the Performance Gap: Results of a Workshop on Addressing Energy, Health and Comfort Needs in a Protected Building

“…For example, one factor that is commonly pointed to as a significant uncertainty in energy modelling (and, hence a contributor to the performance gap) is user occupancy [14,15]; given its variability, stochastic approaches have been proposed for its estimation, with some success (examples include Fritsch et al [16] and Wang et al [14]). However, Ahn and others [15] demonstrate that stochastic methods are not representative of patterns of building are more random (e.g., such as libraries or laboratories), and demonstrate a "random walk" approach to estimating the occupancies of these types of buildings.…”