An Efficient Antenna Design Method Based on Machine Learning–Assisted Hybrid Data Modeling

An efficient antenna design method based on machine learning-assisted hybrid data modeling is proposed. By introducing combined machine learning model based on convolutional neural networks (CNN) and multi-layer perceptron (MLP) as hybrid agent model, the complicated problems can be described and optimized using hybrid optimization algorithm. The effectiveness of the optimization method is verified by the multi-objective decoupling task of patch antenna case.