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Notice of Retraction: Risk prediction model for construction projects based on rough sets and artificial neural networks

Conference Paper


Abstract

  • Combined with the research status of construction safety management and considered of the human, machine and environment, the security control indexes of "wounded rate per thousand" and "ecnomic loss per million cost of project" are used to analysis the influencing factors of the construction project and the indexes system was set up. With introducing information entropy to rough set reduction algorithm, the index system was reduced as the input of the artificial neural networks (ANN). Then, the safety prediction model of construction project was established based on rough sets(RS) and ANN. The testing results show that the proposed system provides not only an effective prediction of the main influencing risk factors for construction projects, but also a reliable tool for safety management. �� 2009 IEEE.

Publication Date

  • 2009

Citation

  • Meng, W., Li, W., Li, J., & Zhang, M. (2009). Notice of Retraction: Risk prediction model for construction projects based on rough sets and artificial neural networks. In 2009 2nd International Conference on Future Information Technology and Management Engineering, FITME 2009 (pp. 428-431). doi:10.1109/FITME.2009.113

Scopus Eid

  • 2-s2.0-77950885095

Start Page

  • 428

End Page

  • 431

Volume

Issue

Place Of Publication

Abstract

  • Combined with the research status of construction safety management and considered of the human, machine and environment, the security control indexes of "wounded rate per thousand" and "ecnomic loss per million cost of project" are used to analysis the influencing factors of the construction project and the indexes system was set up. With introducing information entropy to rough set reduction algorithm, the index system was reduced as the input of the artificial neural networks (ANN). Then, the safety prediction model of construction project was established based on rough sets(RS) and ANN. The testing results show that the proposed system provides not only an effective prediction of the main influencing risk factors for construction projects, but also a reliable tool for safety management. �� 2009 IEEE.

Publication Date

  • 2009

Citation

  • Meng, W., Li, W., Li, J., & Zhang, M. (2009). Notice of Retraction: Risk prediction model for construction projects based on rough sets and artificial neural networks. In 2009 2nd International Conference on Future Information Technology and Management Engineering, FITME 2009 (pp. 428-431). doi:10.1109/FITME.2009.113

Scopus Eid

  • 2-s2.0-77950885095

Start Page

  • 428

End Page

  • 431

Volume

Issue

Place Of Publication