A Machine Learning-Based Approach for Antenna Design Using Class_Reg Algorithm Optimized Using Genetic Algorithm

Microstrip patch antennas are predominantly in use in mobile communication and healthcare. Their performances are even improved, using Split-Ring Resonator cells. But finding the ideal dimensions of the microstrip patch antenna and calculating the correct number and size of the split ring resonator cells consume a lot of time when we use Electromagnetic Simulation software to design first and then simulate. Using the pre-calculated results of certain sets of microstrip patch antennas with split ring resonators, a machine learning model can be trained and hence be used to predict the antenna metrics when the dimensions are specified. When the machine learning algorithms are combined with feature-optimization algorithms such as the Genetic Algorithm, the efficiency and performance can be improved further. Keywords: Machine Learning, Micro-strip Patch Antenna, Genetic algorithm, Split Ring Resonator.