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BIM기반 자동화 데이터 수집기술을 활용한 위험지역 식별 모델
김현수,이현수,박문서,이광표,편재호,Kim, Hyun-Soo,Lee, Hyun-Soo,Park, Moon-Seo,Lee, Kwang-Pyo,Pyeon, Jae-Ho 한국건설관리학회 2010 한국건설관리학회 논문집 Vol.11 No.6
A considerable number of construction disasters occurs on pathway. A safety management in construction sites is usually performed to prevent accidents in activity areas. This means that safety management level of hazards on pathway is relatively minified. Many researchers have introduced that a hazard identification is fundamental of safety management. Thus, algorithms for helping safety managers' hazardous area identification is developed using automated data collection technology. These algorithms primarily search potential hazardous area by comparing workers' location logs based on real-time locating system and optimal routes based on BIM. And potential hazardous areas is filtered by identified hazardous areas and activity areas. After that, safety managers are provided with information about potential hazardous areas and can establish proper safety countermeasures. This can help improving safety in construction sites.
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사례기반추론 코스트 모델의 정성변수 속성가중치 산정방법
이현수,김수영,박문서,지세현,성기훈,편재호,Lee, Hyun-Soo,Kim, Soo-Young,Park, Moon-Seo,Ji, Sae-Hyun,Seong, Ki-Hoon,Pyeon, Jae-Ho 한국건설관리학회 2011 한국건설관리학회 논문집 Vol.12 No.1
For construction projects, the importance of early cost estimates is highly recognized by the project team and sponsoring organization because early cost estimates are frequently a foundation of business decisions as well as a basis for identifying any changes as the project progresses from design to construction. However, it is difficult to accurately estimate construction cost in the early stage of a project due to various uncertainties in construction. To deal with these uncertainties, cost estimates should be made several times over the course of the project. In particular, early cost estimates are essential process for successful project management. For accurate construction cost estimates, it is necessary to compare cost estimates with actual costs based on historical project data. In this context, case-based reasoning (CBR), which is the process of solving new problems based on the solutions of similar past problems, can be considered as an effective method for cost estimating. To obtain this, it is also required to define the attribute similarities and the attribute weights. However, no existing method is capable of determining attribute weights of qualitative variables. Consequently, it has been a well-known barrier of accurate early cost estimates. Using Genetic Algorithms (GA), this research suggests the method of determining the attribute weight of qualitative variables. Based on building project case studies, the proposed methodology was validated.
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