Abstract: With the construction of the Western region of China and the development of “ the Belt and Road Initia- tives”,there is an urgent need to develop some major “lifeline” projects such as transportation,mining and water con- servancy. Deep buried tunnels are often the key control projects for these lifeline projects. Limited to geological,topo- graphical and natural environmental conditions,the TBM method is the preferred choice for deep tunnel excavation in terms of construction period,cost and technical progress. The adaptability of deep tunnel TBM is affected by many fac- tors,making it difficult to conduct an effective and quantitative evaluation. The main influencing factors are unfavorable geology,such as inrush water,large soft rock deformation,fault fracture zone,rock burst,etc. In addition,the design of the tunnel and the geological conditions of the tunnel site also have an important impact on the selection of TBM. The artificial intelligence method has the outstanding features of being able to analyze the influence of complex factors and dealing with complex problems,and can be used for the effective evaluation of the adaptability of TBM selection. First- ly,based on the analytic hierarchy process ( AHP) and fuzzy comprehensive evaluation method,through the acquisi- tion of TBM selection knowledge,seven indicators which can fully reflect the differences of adaptability,representative- ness and high discrimination are selected. The evaluation index system and fuzzy comprehensive evaluation model of TBM selection adaptability are constructed,and the fuzzy membership function of each evaluation index is determined. Secondly,the weights of three TBM model selection adaptability evaluation indicators are determined by compiling the weights assistant calculation program. Among them,in order to avoid the limitation of single index decision and the de- fect of subjective assumption,a combination of intelligent design theory and decision-making theory is adopted to carry out the quantitative selection of multi-indicator intelligent decision-making. Combining the evaluation model with knowledge,expressing the knowledge in the form of rules,the TBM selection adaptive evaluation knowledge base is constructed. Finally,based on the IDSDP intelligent evaluation and decision system platform,an intelligent evaluation and decision-making system for TBM selection is developed,which provides a new quantitative evaluation method for the deep tunnel TBM selection. The adaptability of TBM selection for Gaoligongshan Railway Tunnel is evaluated by u- sing the decision-making system,and the evaluation results are in good agreement with the actual situation.