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인공지능을 활용한 한옥 부재의 형태 인지방법에 관한 연구 - 한옥 공포를 중심으로 -

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dc.contributor.author김은영-
dc.contributor.author김미경-
dc.contributor.author지승열-
dc.contributor.author전한종-
dc.date.accessioned2022-07-09T19:21:50Z-
dc.date.available2022-07-09T19:21:50Z-
dc.date.created2021-05-14-
dc.date.issued2019-04-
dc.identifier.urihttps://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/147954-
dc.description.abstractThe largest earthquake occurred in Gyeong-ju. The damage investigation of cultural reconstruction is based on the analysis of the cause of damage such as analysis of structure and non - structural factors. It is not enough to analyze and compare the correlation between building data and seismic data, but rather to estimate the damage caused by the earthquake that will occur in the future. The purpose of this study is to examine the artificial intelligence processing method of Hanok for interpreting and predicting the relationship between seismic data on the shape of hanok using artificial intelligence techniques.-
dc.language한국어-
dc.language.isoko-
dc.publisher대한건축학회-
dc.title인공지능을 활용한 한옥 부재의 형태 인지방법에 관한 연구 - 한옥 공포를 중심으로 --
dc.title.alternativeA Study on the Method for Visual Perception of Hanok Components Form through Artificial Intelligence - Focusing on the Hanok Bracket System --
dc.typeArticle-
dc.contributor.affiliatedAuthor전한종-
dc.identifier.bibliographicCitation대한건축학회 2019년도 춘계학술발표대회논문집, v.39, no.1, pp.100 - 101-
dc.relation.isPartOf대한건축학회 2019년도 춘계학술발표대회논문집-
dc.citation.title대한건축학회 2019년도 춘계학술발표대회논문집-
dc.citation.volume39-
dc.citation.number1-
dc.citation.startPage100-
dc.citation.endPage101-
dc.type.rimsART-
dc.type.docTypeProceeding-
dc.description.journalClass3-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassother-
dc.subject.keywordAuthor인공지능-
dc.subject.keywordAuthor한옥부재-
dc.subject.keywordAuthor공포-
dc.subject.keywordAuthor형태인지-
dc.subject.keywordAuthorArtificial Intelligence-
dc.subject.keywordAuthorHanok Components-
dc.subject.keywordAuthorBracket System-
dc.subject.keywordAuthorVisual Perception-
dc.identifier.urlhttps://www.dbpia.co.kr/journal/articleDetail?nodeId=NODE08753768-
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