Risk assessment has always been an important part of safety risk research in tunnel and underground engineering. Owing to the characteristics of tunnel construction, to achieve an expected risk control effect, it is necessary to carry out accurate risk assessment research according to the risk assessment concept based on the entire tunnel construction process. At present, because of the frequent occurrences of safety accidents, a variety of risk assessment models have been proposed for different tunnel projects such as subways and railway tunnels, which can be roughly classified into two types: probability-based and fuzzy set theories. However, the existing models may be more suitable for the construction stage, and the design stage lacks a reliable and practical fuzzy risk assessment method. Therefore, based on fuzzy set theory and similarity measure theory, a risk assessment model is proposed to adapt to the characteristics that the risk information is difficult to quantify the fuzziness in the design phase. Firstly, new ideas of fuzzy risk analysis are proposed to overcome deficiencies in existing methods; secondly, a new similarity measure is constructed; then fusing multi-source fuzzy information based on evidence theory, the relationship between similarity measure and mass function is established. Finally, the new method is applied to the Yuelongmen tunnel. Results show that the concept of risk control and the risk assessment model are feasible.
Analysis of the Algorithm for Medical Diagnostic Reasoning based on the New Similarity Measure of Fuzzy Set