Artificial Neural Network Model Analysis of Tunable Annular-Ring Microstrip Patch Antenna

In recent years, the use of artificial neural networks (ANNs) in wireless communication engineering has become more and more common. This study presents the basic radial function (RBF) for the analysis of an adjustable annular ring microstrip antenna, as well as the basic idea of the cavity model in conjunction with artificial neural networks. We must first validate the proposed methodology before assessing the influence of the physical properties on the resonance frequency. We'll then look at the effects of the different patch options. There is a striking agreement between the outputs of the brain models and the experimental results published in the literature.