한국건설관리학회논문집 (Korean Journal of Construction Engineering and Management)

  • 제24권1호
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  • Pages.61-70
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  • 2023
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  • 2005-6095(pISSN)
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  • 2465-9703(eISSN)
한국건설관리학회 (Korea Institute of Construction Engineering and Management)
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온톨로지 기반 최적 리모델링 대안선정 방법

Ontology based Green Remodeling Alternative Selection Method

  • Ji, Hyunsuh (Yeonwoo Technology) ;
  • Cho, Kyuman (Department of Architectural Engineering, Chosun University) ;
  • Kim, Taehoon (Department of Architectural Engineering, Chosun University)
  • 투고 : 2022.10.19
  • 심사 : 2023.01.17
  • 발행 : 2023.01.31
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초록

경제적인 측면이나 친환경적인 측면의 사유로 인해, 노후 건축물을 대상으로 그린리모델링 사업이 활발하게 진행되고 있다. 한편, 그린리모델링 사업을 추진하는 과정에서, 기존에는 설계자 및 엔지니어의 주관적 경험 및 지식에 기반하여 그린리모델링 계획이 개발되어 왔고, 이로 인해 경제성 등의 측면에서 효율적인 의사결정이 부족했다. 이에 본 연구에서는 노후 건축물의 속성을 분석하고 이에 따른 적정 리모델링 계획을 제안할 수 있는 온톨로지 기반 그린리모델링 의사결정 지원 모델을 구축하였다. 개발된 모델에서는 건축물의 기본 속성을 입력하면 온톨로지를 통한 웹검색을 기반으로 패시브 액티브 요소로 구성된 적정 리모델링 계획을 제공할 수 있다. 연구를 통해 개발된 결과물을 활용하면, 리모델링 사례의 증가에 따른 웹기반의 메타 데이터 검색을 통해 보다 객관적인 적정 리모델링 대안에 대한 의사결정 지원이 가능할 것으로 기대된다.

Due to economic or environmental reasons, green remodeling projects for old buildings are being actively carried out. Meanwhile, in the process of performing the green remodeling, the plan of green remodeling including passive and active elements has been decided based on the subjective experience and knowledge of engineers currently. Therefore, in this study, an ontology-based green remodeling decision-making support model, which can analyze the properties of old buildings and suggest appropriate remodeling plans, was established. In the developed model, once the basic properties of a building are entered, an appropriate remodeling plan composed of passive and active elements can be provided. By utilizing the results developed through the research, it is expected that it will be possible to support decision-making on more objective and appropriate remodeling alternatives development through web-based meta data search in accordance with the accumulation in remodeling cases.

키워드

과제정보

본 연구는 한국연구재단의 지원으로 수행된 연구(NRF-2020R1A22009799) 결과의 일부임.

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