| 논문명 |
확률적 모델을 이용한 재실 인원 예측 / Stochastic Model Based Prediction of Occupants' Presence in Residential Apartment Buildings |
| 저자명 |
김영진 (Kim Young-Jin) ; 박철수(Park Cheol-Soo) |
| 수록사항 |
대한건축학회논문집 계획계, v.25 n.03 (2009-03) |
| 주제어 |
환기 ; 불확실성 ; 공동주택 ; 마르코브 체인 ; 민감도 분석 ; 몬테카를로 ; Ventilation ; Uncertainty ; Apartment Buildings ; Markov Chain ; Sensitivity Analysis ; Monte-Carlo |
| 요약2 |
With the recent increased expectation of better indoor environment, the need of reliable ventilation simulation has become significant. Such simulation results vary with uncertain parameters including (1) stochastic nature of weather, (2) occupants' behavior, (3) building components, (4) uncertainties in the simulation parameters. It has been recognized that the occupant's presence and behavior significantly influenced the prediction of the ventilation rates as well as indoor air quality. The paper shows that the occupant's schedule is more influential than other inputs to ventilation simulation. In light of this, the paper present a prediction method of occupant's presence employing Markov Chain. A typical of a residential building consisting of a master room, two bedrooms, a living room and kitchen was chosen for the study. The occupant's presence for 30 families were obtained. Based on the collected data, a transition probability matrix was developed to predict the future state from the current state. The paper shows that the proposed method performs better than a conventional deterministic approach (using occupant's schedule). |
