Detailed Information
Cited 0 time in 
Cited 0 time in 
Cited 0 time in
Metadata Downloads
기계학습 모델을 이용한 거주자의 창문 개폐 행위 예측에 관한 연구Predicting the Occupant Window Control Behavior Using Machine Learning Models
- Other Titles
- Predicting the Occupant Window Control Behavior Using Machine Learning Models
- Issue Date
- Apr-2018
- Publisher
- 대한건축학회
- Keywords
- 거주자 행동; 창문 개폐; 기계학습; 환기; 공동주택; Occupant behavior; Window control; Machine learning; Ventilation; Residential building
- Citation
- 2018년 대한건축학회 춘계학술발표대회논문집, v.38, no.1, pp.458 - 459
- Indexed
- OTHER
- Journal Title
- 2018년 대한건축학회 춘계학술발표대회논문집
- Volume
- 38
- Number
- 1
- Start Page
- 458
- End Page
- 459
- Abstract
- 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.
- Files in This Item
- Go to Link
- Appears in
Collections - 서울 공과대학 > 서울 건축공학부 > 1. Journal Articles
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
Related Researcher
- Park, Jun Seok
- COLLEGE OF ENGINEERING (SCHOOL OF ARCHITECTURAL ENGINEERING)