Intelligent Design of Arbitrary Bandstop FSS Through Deep Learning and Genetic Algorithm

Frequency selective surface (FSS) is used for electromagnetic radiation suppression due to its unique filtering characteristics. However, it still takes some experience and time to design a FSS structure with a specific stopband for actual shielding requirements. In this paper, a method based on deep learning and elite genetic algorithm is proposed, which can realize the automatic design of arbitrary bandstop FSS structure. This method only relies on a basic FSS model and some parameter scanning data to achieve the final design, reducing the need for design experience and the labor cost of repeated iterations.