Multi-attribute fire safety evaluation of subway station based on FANP – FGRA – Cloud model

Abstract

With the development of subway network, the fire safety of station is affected by many factors in the operation process. But there seem to be few studies developing quantitative models to evaluate fire safety of subway station. The aim of this study is to develop a multi-attribute hybrid method by combining Fuzzy Analytic Network Process (FANP), Fuzzy Grey Relational Analysis (FGRA) with Cloud model. This research sorts out and identifies high-frequency hazard factors associated with fire accidents of station from personal, equipment, environmental and management aspects comprehensively, and explores dependences and interactions among them simultaneously. Seven typical transfer stations of Changsha subway network in China are studied by using the proposed approach, and the results show that: (1) the fire safety order from the best to the worst determined is FBH (A2), SWGY (A7), CSRS (A6), YWZ (A1), HTL (A5), HJT (A4) and WYGC (A3); (2) through comparing the results obtained by the proposed method with that determined fuzzy TOPSIS and fuzzy sum weighted method, it is proved that the method developed in this study is reliable and effective; and (3) sensitivity analysis indicates that the ranking order of stations is influenced by fluctuation of criterion and sub-criterion weights. These findings concentrate on providing a new sight for identification of hazard factors and quantitative evaluation regarding the fire safety of stations, so as to prevent this type of security accidents and minimize damages caused by this.