S-Parameters Prediction of a Cavity Filter Based on BP Neural Network Algorithm

The critical role of electromagnetic multiphysics simulation in accurately simulating real-world scenarios cannot be overstated and COMSOL is a powerful multiphysics simulation software. Our work leverages COMSOL to repeatedly simulate a typical cavity filter model, resulting in 340 distinct S-parameter curves. Each curve corresponds to a unique set of filter parameters as inputs. The simulation inputs and outputs were integrated into a Backpropagation (BP) neural network for training and prediction. This integration of neural network and data-driven methodologies not only reduces the computational time of electromagnetic multiphysics simulation from two hours to two seconds but also yields accurate numerical solutions, which difference with COMSOL simulation results is only 4%. The framework can be innovatively designed for rapid prediction and analysis of cavity filter performance.