Decision support analysis for safety assurance in metro construction base on Fuzzy Bayesian Networks

This paper presents a novel and systemic decision support model based on Fuzzy Bayesian Networks (FBN) for safety assurance in metro construction. An expert confidence index is proposed for the fuzzification in probability assessment of basic risk factors, aiming to ensure the reliability of collected data during the expert investigation. A fuzzy-based decision approach, with the capacity of forward reasoning, sensitivity analysis and backward reasoning, is developed based on Bayesian inference. The safety assurance progress is extended to the entire life cycle of risk-prone events, including the pre-accident, during-construction continuous and post-accident control. A typical hazard concerning the tunnel leakage in the Wuhan Yangtze Metro Tunnel construction is presented in a case study. The results demonstrate the feasibility of the proposed method and its application potential. The proposed method can be used as a decision support tool to provide guidelines for safety assurance in metro construction, and thus increase the likelihood of a successful project in a complex environment.