A formwork method selection model based on boosted decision trees in tall building construction

Yoonseok Shin, Taehoon Kim, Hunhee Cho, Kyung In Kang

Research output: Contribution to journalArticlepeer-review

53 Citations (Scopus)

Abstract

In tall building construction with reinforced concrete structures, the appropriate selection of the formwork method is a crucial factor in successful project completion. The selected formwork method significantly influences the project duration and cost as well as subsequent activities. However, in practice, this selection has depended mainly on the subjective and intuitive opinions of practitioners with restricted experience. Therefore, we propose a formwork method selection model based on boosted decision trees to assist the practitioner's decision making. To evaluate its performance, the proposed model was compared with an artificial neural network model and a decision tree model. The results showed that the proposed model was slightly more accurate than the others in the selection of the formwork method. Moreover, the result also demonstrated the advantages of the new method, i.e., single parameter setting, accuracy and stability improvement, and a comprehensible process in decision making.

Original languageEnglish
Pages (from-to)47-54
Number of pages8
JournalAutomation in Construction
Volume23
DOIs
Publication statusPublished - 2012 May

Bibliographical note

Funding Information:
This research was supported by a grant(code#09 R&D A01) from High-Tech Urban Development Program funded by the Ministry of land, transport and maritime affairs. Also, this research was supported by a Korea University Grant.

Keywords

  • Boosted decision tree
  • Formwork method
  • Tall building construction

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Civil and Structural Engineering
  • Building and Construction

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