A SIMPLE AND EFFICIENT APPROACH TO TRAIN ARTIFICIAL NEURAL NETWORKS USING A GENETIC ALGORITHM TO CALCULATE THE RESONANT FREQUENCY OF AN RMA ON THICK SUBSTRATE

摘要

Both genetic algorithms (GAs) and artificial neural networks (ANNs) have been used in the field of computational electromagnetics as the most powerful optimizing tools. In this paper, a simple and efficient method is presented to handle the problem of competing convention while training an ANN by using a GA, This technique is applied to calculate the resonant frequency of a thick-substrate rectangular microstrip antenna (RMA), The training time is less than that of a normal feed-forward backpropagation algorithm. The measured results are in very good agreement with experimental results.