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dc.contributor.author박준석-
dc.date.accessioned2020-11-04T01:10:55Z-
dc.date.available2020-11-04T01:10:55Z-
dc.date.issued2019-11-
dc.identifier.citation한국건축친환경설비학회 추계학술발표대회 2019, Page. 79-80en_US
dc.identifier.urihttp://www.auric.or.kr/User/Rdoc/DocRdoc.aspx?returnVal=RD_R&dn=388841#.X4U1ZtAzaUl-
dc.identifier.urihttps://repository.hanyang.ac.kr/handle/20.500.11754/155178-
dc.description.abstractThe purpose of this study is to predict the window opening behavior to reduce the energy consumption in buildings. Window Opening & closing is most preferred behavior to adjust their indoor environment. However these behavior causes an increase in energy consumption in the building In the previous study, the environmental factors (temperature, humidity, etc.) were attempted to directly predict the window opening using machine learning techniques. Too many factors were applied to machine learning to try to make predictions, so I found that there was a problem in actually making prediction tools. Therefore, this study analyzed the flow of factors and principal component analysis to reduce the factors. Based on the result, the process of deleting factors or merging collinear factors will leave only the minimum number of factors to use in the prediction tool.en_US
dc.language.isoko_KRen_US
dc.publisher한국건축친환경설비학회en_US
dc.subject창문 개방en_US
dc.subject거주자en_US
dc.subject행동예측en_US
dc.subject머신러닝en_US
dc.subjectWindow openingen_US
dc.subjectOccupantsen_US
dc.subjectBehaviour Predictionen_US
dc.subjectMachine learningen_US
dc.title거주자의 자연 환기 행위 예측을 위한 주성분분석en_US
dc.title.alternativeDerivation of PCA(Principal Component Analysis) Factors for Predicting Natural Ventilation Behaviour of Occupantsen_US
dc.typeArticleen_US
dc.relation.page1-2-
dc.contributor.googleauthor안영민-
dc.contributor.googleauthor고보민-
dc.contributor.googleauthor박준석-
dc.contributor.googleauthorAn, Young-Min-
dc.contributor.googleauthorKo, Bo-Min-
dc.contributor.googleauthorPark, Jun-Seok-
dc.sector.campusS-
dc.sector.daehakCOLLEGE OF ENGINEERING[S]-
dc.sector.departmentDEPARTMENT OF ARCHITECTURAL ENGINEERING-
dc.identifier.pidjunpark-
Appears in Collections:
COLLEGE OF ENGINEERING[S](공과대학) > ARCHITECTURAL ENGINEERING(건축공학부) > Articles
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