Application of Artificial Neural Network Base Enhanced MLP Model for Scattering Parameter Prediction of Dual-band Helical Antenna

Many design optimization problems have that seek fast, efficient and reliable based solutions. In such cases, artificial intelligence-based modeling is used to solve costly complex problems. This study on the of a multiband helical antenna using Latin hypercube sampling (LHS) method reduced data enhanced multilayer perceptron (eMLP). The proposed dual-band has resonance frequencies 2.4 GHz 2.75 GHz. structure neural network (ANN) was tested 4 different training algorithms maximum 10 MLP architectures determine most suitable model in simple quick way. Then, performance comparison with other ANN networks made confirm success model. Considering high cost simulations, it clear will save lot time. addition, thanks selected model, wide range can be done minimum data. When target prediction are compared, seen these overlap large extent. As result study, 125 samples used, were as accurate an electromagnetic (EM) simulator for input parameters selected.