Designing of Dual Band F-Shaped RFID Antenna Using Machine Learning Techniques

Abstract

In this paper, using machine learning, a dual-band F-shaped RFID antenna is designed to operate in 867MHz UHF and 2.45GHz WLAN bands. The study's dataset was consisting of a total of 625 samples, and this was received from the simulation software as a consequence of the parametric analysis of the design parameters for the antenna. The success of the algorithms was compared after six of the most popular machine learning algorithms were applied to the same parameters. The Random Forest algorithm, which has a 99.96% for R2 score and a mean squared error value of 0.0004, has been used to predict the input port scattering parameter. With the best results obtained from this technique, the antenna operating at the desired frequencies was designed.