Operating Frequency Prediction of Annular Ring Microstrip Antenna Using Extreme Learning Machine

This article presents, Machine Learning-based proficient and quick, Extreme Learning Machine (ELM) procedure to predict the operating frequency of the Annular ring compact microstrip antenna (ARCMA)in the range of 0.95–5.76 GHz. As per UHF and SHF bands, 100 data samples are collected through simulation using CST by varying the proportion of inner radius to an outer radius of ARCMA’s. Arbitrarily 90 samples were utilized to set up the ELM model, and the remaining 10 data samples were utilized to test the model. It was observed that the simulated and predicted operating frequencies of the ARCMA’s are exceptionally near one another and can be used to design an annular ring microstrip antenna for UHF and SHF band applications.