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기계학습 모델을 이용한 거주자의 창문 개폐 행위 예측에 관한 연구
Predicting the Occupant Window Control Behavior Using Machine Learning Models
- 정봉찬;
- 최희원;
- 정진화;
- 채영태;
- 박준석
초록
The purpose of this study was to predict individual occupant window control behavior in a residential building using a machine learning model. Outdoor and indoor environmental conditions and window states of 23 sample housing units were measured every 10 minutes for 10 months. The occupants showed different window opening behavior even under identical environmental conditions. Three machine learning models, k-Nearest Neighbors (KNN), Random Forest (RF) and Artificial Neural Networks (ANN) were used to predict window states of 23 individual occupants. The results shows that machine learning methods are appropriate to predict occupants' individual window opening behavior.
키워드
거주자 행동; 창문 개폐; 기계학습; 환기; 공동주택; Occupant behavior; Window control; Machine learning; Ventilation; Residential building
- 제목
- 기계학습 모델을 이용한 거주자의 창문 개폐 행위 예측에 관한 연구
- 제목 (타언어)
- Predicting the Occupant Window Control Behavior Using Machine Learning Models
- 저자
- 정봉찬; 최희원; 정진화; 채영태; 박준석
- 발행일
- 2018-04
- 유형
- Proceeding
- 저널명
- 2018년 대한건축학회 춘계학술발표대회논문집
- 권
- 38
- 호
- 1
- 페이지
- 458 ~ 459