As the lifeline of urban traffic

the health evaluation of rail transit has become increasingly important. In recent years

the models to estimate the health of tunnel engineering was mainly concentrated on highway tunnels

mountain tunnels or the operation stage of rail transit tunnel. It is still lack of models to assess the geological risk in the design and construction stages of rail transit. Based on a large number of literatures and standards

a risk criteria including 11 geological risk sources and 40 identification indexes was set up

in which four risk levels

i.e.

small

weak

medium and strong

was utilized to evaluate the overall geological risk. The weights of each index were determined by BP neural network and more flexible multiplication scale method. Then

a fuzzy variable evaluation model for geological risk in rail transit tunnel was established. The time factor set was also added into the fuzzy variable evaluation model to realize the dynamic evaluation of geological risk which can help to estimate the risk during the whole life of rail transit. Finally

the model was proved by the calculating results based on the preliminary geological data of a proposed rail transit line in Guangzhou. The risk levels evaluated by the model were consistent with the insitu measurement and geological survey.