A CASE STUDY ONHGNNA BASED PREDICTION OF RESONANT FREQUENCY FOR SQUARE LOOP FREQUENCY SELECTIVE SURFACE

Abstract

Frequency Selective Surface is a well accredited scientific tag in present day communication engineering. Investigations on Frequency Selective Surface applications haveexhibited sharp inclination of research interest among researchers worldwide. In due course of action several new softwarefor Frequency Selective Surface simulationwere reported, but they failed to furnish satisfactory results in terms of computational complexity, in simulation related time consumption or even in accuracy. In order to sustain the progression of Frequency Selective Surface research the authors experienced the earnestness to deploy soft computing tool for simulation of different Frequency Selective Surface structures. Accordingly, in their earlier research attempts the authors demonstrated how Genetic Algorithm or Particle Swarm Optimization can be articulated to train the Artificial Neural Network for the simulation of Frequency Selective Surface. Here the authors tender a hybridized algorithm to amplify the easiness of simulating Frequency Selective Surface square loop structure. The authors humbly admit that the results are immensely satisfying compared to their software counterpart.