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Application of Support Vector Machines in Assessing Conceptual Cost Estimates |
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| Authors: | Sung-Hoon An U-Yeol Park Kyung-In Kang Moon-Young Cho Hun-Hee Cho |
| Affiliation: | 1Senior Researcher, Institute of Construction Technology, Hyundai Engineering and Construction, 102-4 Mabuk-Dong, Giheung-Gu, Yongin-Si, Gyunggi-Do 449-716, Korea. E-mail: shan7208@hanmail.net 2Assistant Professor, Dept. of Architecture Engineering, Andong National Univ., 388 Songchon-Dong, Andong-Si, Kyeongsangbuk-Do 760-749, Korea. E-mail: wypark@andong.ac.kr 3Professor, Dept. of Architecture Engineering, Korea Univ., 5Ga, Anam-Dong, Sungbuk-Gu, Seoul 136-701, Korea. E-mail: kikang@korea.ac.kr 4Senior Research Fellow, Korea Institute of Construction Technology, 2311 Daewha-Dong, Ilsan-Gu, Goyang-Si, Gyeonggi-Do 411-712, Korea. E-mail: mycho@kict.re.kr 5Assistant Professor, Division of Architecture and Ocean Space, Korea Maritime Univ., 1 Dongsam-Dong, Yeongdo-Gu, Busan 606-791, Korea (corresponding author). E-mail: hhcho@hhu.ac.kr |
| Abstract: | Total conceptual cost estimates and the assessment of the quality of these estimates are critical in the early stages of a building construction project. In this study, the support vector machine (SVM) model for assessing the quality of conceptual cost estimates is proposed, and the application of SVM in construction areas is investigated. The results show that the SVM model assessed the quality of conceptual cost estimates slightly more accurately than the discriminant analysis model. This shows that using the SVM has potential in construction areas. In addition, the SVM model can assist clients in their evaluation of the quality of the estimated cost and the probability of exceeding the target cost, and in their decision on whether or not it is necessary to seek a more accurate estimate in the early stages of a project. |
| Keywords: | Cost estimates Assessments Artificial intelligence Korea Construction equipment |