A Novel Risk Assessment Model in Tunnel Leakage by Using Cloud Model and Dempster-Shafer Evidence Theory
Kai Guo, Limao Zhang · Construction Research Congress 2020 · 2020
This paper proposes a risk perception method combing the cloud model, Dempster-Shafer evidence theory, expecting to better perceive and assess the leakage risk of tunnel construction projects. This proposed method takes advantage of the cloud model theory that transforming qualitative to quantitative. The membership degree calculated from the cloud model is transformed into the accuracy of the indicator for each level of the leakage risk. Treating the membership degree as the evidence of the Dempster-Shafer (D-S) evidence theory and further fusing the evidence of risk status of the leakage in the tunnel construction with the Dempster's evidence fusion rules, the risk grades of the leakage disease can be confirmed. A section of the tunnel construction is utilized as a case study to test the applicability and effectiveness of the proposed approach. Through the case study, this proposed leakage assessing method is demonstrated capable of accurately perceiving the risk status of the leakage in tunnel construction projects, and thus preventive measurements can be adopted according to the corresponding risk status grades and the rank of different influencing factors.