In order to improve the machining accuracy of the five-axis machine tool, a dynamic error model for five-axis machine tool was proposed based on AFSA-ACO-BPN algorithm.The optimization of modeling variables was completed by establishing a grey relational analysis model, and the dynamic fusion of AFSA and ACO-BPN was carried out. The experimental results show that the predicted results of the proposed method is in good agreement with the measured results. The method comprehensively reflects the influence of different cutting conditions, improves the robustness of the error model, and provides a theoretical basis for improving the machining accuracy of the machine tool.