In order to realize accurate neural network modeling for the dual notch ultra-wideband(UWB)antenna, a modeling method using the improved fruit fly algorithm (FOA) to optimize the generalized regression neural network (GRNN) is proposed. This method achieves the improvement of the fruit fly algorithm by expanding the search range of fruit flies, introducing adjustment items into the taste judgment formula, and using the improved fruit fly algorithm to optimize the smoothing factor of GRNN. In this way, the fruit fly algorithm can be prevented from falling into local optimum and the model prediction accuracy can be improved. This method is used in the establishment of the dual notch UWB antenna model, and the antenna S₁₁ parameters and voltage standing wave ratio V_VSWR parameters are predicted. Experimental results show that, compared with the FOA-GRNN modeling method and the GRNN modeling method, the maximum relative error of the S₁₁ parameter is reduced by 91.08% and 99.14%, respectively, and the maximum relative error of the V_VSWR parameter is reduced by 98.36% and 99.18%, respectively. The accuracy of UWB antenna modeling is improved, and the method feasibility is verified.