Korean Journal of Construction Engineering and Management (한국건설관리학회논문집)

Korea Institute of Construction Engineering and Management (한국건설관리학회)
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A Study on Estimating Construction Cost of Apartment Housing Projects Using Genetic Algorithm-Support Vector Regression

유전 알고리즘 - 서포트 벡터 회귀를 활용한 공동주택 공사비 예측에 관한 연구

  • Nan, Jun (Department of Frontier Architectural and Urban Environmental Engineering, Hanyang University) ;
  • Choi, Jae-Woong (Samsung Everland) ;
  • Choi, Hyemi (Department of Frontier Architectural and Urban Environmental Engineering, Hanyang University) ;
  • Kim, Ju-Hyung (Department of Frontier Architectural and Urban Environmental Engineering, Hanyang University)
  • 남군 (한양대학교 첨단건축도시환경공학과) ;
  • 최재웅 (삼성에버랜드) ;
  • 최혜미 (한양대학교 첨단건축도시환경공학과) ;
  • 김주형 (한양대학교 첨단건축도시환경공학과)
  • Received : 2014.02.10
  • Accepted : 2014.04.23
  • Published : 2014.07.31
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Abstract

The accurate estimation of construction cost is important to a successful development in construction projects. In previous studies, the construction cost are estimated by statistical methods. Among the statistical methods, support vector regression (SVR) has attracted a lot of attentions because of the generalization ability in the field of cost estimation. However, despite the simplicity of the parameter to be adjusted, it is not easy to find optimal parameters. Therefore, to build an effective SVR model, SVR's parameters must be set properly without additional data handling loads. So this study proposes a novel approach, known as genetic algorithm (GA), which searches SVR's optimal parameters, then adopt the parameters to the SVR model for estimating cost in the early stage of apartment housing projects. The aim of this study is to propose a GA-SVR model and examine the feasibility in cost estimation by comparing with multiple regression analysis (MRA). The experimental results demonstrate the estimating performance based on the percentage of estimations within 25% and find it can effectively do the accurate estimation without through the trial and error process.

건축 프로젝트에서 초기단계에서의 정확한 공사비 예측은 성공적인 프로젝트의 중요한 요소이다. 기존의 연구에서 공사비를 예측하기 위한 방법으로 통계학적인 방법이 활용되었다. 통계학적 방법 중 서포트 벡터 회기분석은 비용예측 분야에서 뛰어난 일반화 능력으로 많은 주목을 받고 있다. 하지만 서포트 회귀분석은 조정해야 할 파라미터가 단순함에도 불구하고 최적의 파라미터를 결정하는 방법은 시행착오적인 방법을 적용해야 하는 문제점이 있었다. 따라서 최적의 파라미터를 보다 효율적으로 결정하기 위해 본 연구에서는 유전 알고리즘을 적용하고, 이를 통해 서포트 벡터 회귀를 효율적으로 활용한 공사비 예측이 가능 할 것이다. 본 연구의 목적은 유전 알고리즘과 서포트 벡터 회귀를 활용하여 공동주택의 프로젝트 초기 기획단계의 공사비 예측모델을 구축하는 것이다. 유전 알고리즘을 통해 최적의 파라미터를 찾아내고, 이를 서포트 벡터 회귀모델에 적용시켜 공사비를 예측하였다.

Keywords

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