The traditional model updating methods based on sensitivity analysis can not determine the appropriate design parameters to be updated,and most of the model updating methods independent of sensitivity analysis are complex with large computation.In this paper,a model updating method based on parameters is adopted,and a BP neural network optimized by genetic algorithm is introduced.Then,with the structural dynamic eigen vector as the input,the updated design parameters are directly obtained.The parameters are then used to obtain the structural dynamic eigen vector error of the updated finite element model,and the error minimization is taken as the objective function to implement iterative resolution,thus determining the final updated design parameters.Finally,a 3- span continuous beam model is tested.The results prove that the proposed method is accurate and effective.