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PE pipeline is widely used in urban gas pipe network. The carrying capacity of PE pipe with local thinning defects is an important means to ensure its safe operation.Firstly, the initial elastic modulus and yield stress are fitted by the finite element method to obtain the carrying capacity of internal pressure, bending moment and axial force, the BP neural network model including relative depth C/T, relative axial length 2A/√RT, relative circumferential angle 2θ/π and dimensionless parameters c, and combined with GA optimized BP neural network model. It can be found: the predicted value of the model is relatively consistent with the simulation results, which shows that the method of GA optimization of the BP neural network model is feasible,which provides an effective method for the intelligent safety evaluation of the PE pipeline with local thinning defects. [ABSTRACT FROM AUTHOR]