Multi-Layer FSS Prediction Based on Machine Learning

This paper presents a machine learning-based method for predicting the electromagnetic properties of multilayer structures. The complexity introduced by the coupling of these layers is addressed through a Variational Autoencoder (VAE) network structure. This approach establishes a connection between electromagnetic property data and physical structure data, significantly reducing the computational time required compared to conventional simulation software.