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Knowledge-based diagnosis model for PCM executing problems in public construction

Author

Listed:
  • Ching-Hwang Wang
  • Chia-Chang Tsai
  • Yi-Yen Cheng

Abstract

A knowledge-based diagnosis model for PCM executing problems in Taiwan public construction is proposed by using a new fuzzy-neural approach. The diagnosis model confirms the causalities of the critical executing problems. By inputting the fuzziness of semantic description of the problems in the design phase this model can deduce the corresponding influence of the problems in the construction phase. The gravity of the problem is measured by the specific lagging percentage of estimated pricing progress. Finally, the data is integrated into a database management system to facilitate application, so as to make this diagnosis model an efficient instrument for public construction management.

Suggested Citation

  • Ching-Hwang Wang & Chia-Chang Tsai & Yi-Yen Cheng, 2007. "Knowledge-based diagnosis model for PCM executing problems in public construction," Construction Management and Economics, Taylor & Francis Journals, vol. 25(2), pages 129-142.
    • Handle: RePEc:taf:conmgt:v:25:y:2007:i:2:p:129-142
    DOI: 10.1080/01446190600799091
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    Cited by:

    1. Dengke Yu & Jay Yang, 2018. "Knowledge Management Research in the Construction Industry: a Review," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 9(3), pages 782-803, September.

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