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.
| Original language | English |
|---|---|
| Pages (from-to) | 259-264 |
| Number of pages | 6 |
| Journal | Journal of Computing in Civil Engineering |
| Volume | 21 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 2007 Jun 22 |
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Keywords
- Artificial intelligence
- Assessments
- Construction equipment
- Cost estimates
- Korea
ASJC Scopus subject areas
- Computational Theory and Mathematics
- Computer Science Applications
- Civil and Structural Engineering
Cite this
Application of support vector machines in assessing conceptual cost estimates. / An, Sung Hoon; Park, U. Yeol; Kang, Kyung In; Cho, Moon Young; Cho, Hun Hee.
In: Journal of Computing in Civil Engineering, Vol. 21, No. 4, 22.06.2007, p. 259-264.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Application of support vector machines in assessing conceptual cost estimates
AU - An, Sung Hoon
AU - Park, U. Yeol
AU - Kang, Kyung In
AU - Cho, Moon Young
AU - Cho, Hun Hee
PY - 2007/6/22
Y1 - 2007/6/22
N2 - 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.
AB - 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.
KW - Artificial intelligence
KW - Assessments
KW - Construction equipment
KW - Cost estimates
KW - Korea
UR - http://www.scopus.com/inward/record.url?scp=34250658949&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=34250658949&partnerID=8YFLogxK
U2 - 10.1061/(ASCE)0887-3801(2007)21:4(259)
DO - 10.1061/(ASCE)0887-3801(2007)21:4(259)
M3 - Article
AN - SCOPUS:34250658949
VL - 21
SP - 259
EP - 264
JO - Journal of Computing in Civil Engineering
JF - Journal of Computing in Civil Engineering
SN - 0887-3801
IS - 4
ER -