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Fanpce Technique for Risk Assessment on Subway Station Construction

Author(s):



Medium: journal article
Language(s): Latvian
Published in: Journal of Civil Engineering and Management, , n. 6, v. 25
Page(s): 599-616
DOI: 10.3846/jcem.2019.10373
Abstract:

Risk assessment is critical for the construction of the subway station to improve the risk management and reduce the additional loss. According to field investigation of safe construction, the analytical network process (ANP), fuzzy set theory and fuzzy comprehensive evaluation (FCE), a fuzzy ANP comprehensive evaluation (FANPCE) model was proposed to evaluate the risk of subway station construction in this paper. Twelve key risk factors of subway station construction were identified through literature review and questionnaires. The interdependency among risk factors were illustrated through the network structure of ANP, and then a weight matrix of single risk factors was built by comments and survey results, and the interdependent weight matrix was quantified by integrating the triangular fuzzy number into the ANP. Subsequently, the total risk rank of assessed projects can be quantified though the synthesis of weight matrices with the synthetic operator of FCE. Wu Lu Kou subway station was selected as a case study. The results imply that, construction experience, underground water, and safety consciousness have a substantial influence on construction projects and that the total construction risk of Wu Lu Kou subway station is ranked at I level. Moreover, the loss analysis of the whole construction process verifies this method. This research contributes to developing a FANPCE method to identify the risk factors with high weights, assess the risk rank of projects and appropriately respond to the results. In addition, the developed fuzzy set theory-ANP-FCE integrated network provides stakeholders a consolidated model for the risk evaluation.

Structurae cannot make the full text of this publication available at this time. The full text can be accessed through the publisher via the DOI: 10.3846/jcem.2019.10373.
  • About this
    data sheet
  • Reference-ID
    10354142
  • Published on:
    13/08/2019
  • Last updated on:
    13/08/2019
 
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