Performances Evaluation of Machine Learning Optimization in the Electromagnetic Design of a Metamaterial-Inspired Patch Antenna

This paper explores the application of machine learning techniques to optimize the design of a metamaterialinspired patch antenna.Specifically, the miniaturization of a circular microstrip antenna, is enhanced through AIdriven optimization.Key design parameters are optimized to reduce antenna size while maintaining adequate reflection coefficient values.By exploiting machine learning, the proposed approach enables a significant reduction in computational cost compared to traditional full-wave analysis while preserving design accuracy.The results highlight AI's potential in accelerating the antenna design process and demonstrate its broader applicability in electromagnetic simulations and optimization.