Application of support vector machines in assessing conceptual cost estimates

Sung Hoon An, U. Yeol Park, Kyung In Kang, Moon Young Cho, Hun Hee Cho

Research output: Contribution to journalArticle

48 Citations (Scopus)

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 languageEnglish
Pages (from-to)259-264
Number of pages6
JournalJournal of Computing in Civil Engineering
Volume21
Issue number4
DOIs
Publication statusPublished - 2007 Jun 22

Keywords

  • Artificial intelligence
  • Assessments
  • Construction equipment
  • Cost estimates
  • Korea

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Computer Science Applications

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