Using Machine Learning to predict Characteristics of Microstrip Line and Microstrip Patch Antenna

2024/05/17 by Bharath Balaji, Balaji, Bharath, S. Raghavan +1
Engineering · #Antenna Design and Analysis #Antenna Design and Optimization #FOS: Electrical engineering #Signal Processing (eess.SP) #Wireless Body Area Networks #electronic engineering #information engineering

paper · pdf · doi:10.48550/arxiv.2406.04357

openalex publication_date 2024/05/17 · openalex created_date 2024/06/11 · openalex updated_date 2026/07/28

Abstract

This study, conducted in 2017, explores the use of Machine learning algorithms to predict Characteristics of Transmission Lines such as Impedance or resonance frequency using design parameters of Transmission Lines. Using formulas and equations that define the characteristics of Transmission lines, training data was generated. We trained different models for this dataset. The extent of deviation of predicted output from the actual output was measured in terms of maximum error and average error. This helped determine how well an algorithm worked for a particular transmission line. Further, the best-suited algorithm for each transmission line under consideration was found based on the error

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