Accelerating Antenna Development: The Role of Machine Learning Algorithms

Artificial intelligence (AI) is an emerging technology in in future generation in various technologies. In wireless networks for communications, implementing Machine learning (ML) and deep learning (DL) algorithms helps in order to increase the antenna's efficiency. This paper provides study of antenna design with different machine learning methods, gives better result than conventional methods. Based on current research, this work assists researchers in choosing appropriate algorithms for machine learning to apply on specific antennas at specific frequencies. Application of various antennas is another important component in the study. The study also looks into different antenna design simulators that were used in the research. The review concludes that ML techniques such as K-Nearest Neighbour(KNN), Naive Bayesian, Decision tree(DT), Support Vector Machine(SVM), Random Forest(RF), Extreme Gradient Boosting(XGBoost), Least Absolute Shrinkage and Selection Operator(LASSO) can reduce the overall amount of simulations, quicken the antenna design process, boost computer efficiency.