Prediction of slot-position and slot-size of a microstrip antenna using support vector regression

This article presents a synthesis modeling scheme of rectangular microstrip antenna with support vector regression (SVR) scheme. Here, radiating patch and ground surface is loaded with two asymmetrical slots and two symmetrical slots, respectively. The position of the slots on the radiating patch as well as the size of the slots on the ground surface are predicted using SVR model and artificial neural network (ANN) model. A good convergence rate has been addressed in synthesis model by employing the adaptive step-size. A comparison between SVR model and ANN model is presented where SVR is more accurate and faster than ANN. The suggested SVR approach is also validated by fabricating and characterizing a prototype of microstrip antenna. A very good agreement is observed in measured, simulated, and predicted results. The predicted microstrip antenna has displayed quite good agreement between measured and simulated performance parameters.