Analysis of Optimizing Triple-band Antenna Based on Ensemble Learning Method

An ensemble learning model is employed to optimize the miniaturized triple-band antenna in this paper. Compared with traditional models, ensemble learning combines multiple weak sub-models to get a comprehensive framework that provides accurate prediction from training samples. To explore the effectiveness of the ensemble learning on antenna optimization, a miniaturized tri-band antenna with different parameters' order is adopted as an example. Meanwhile, two machine learning models are given and compared with the same antenna case. Experimental results show that the ensemble learning model can not only ensure the accuracy of optimization, but also has good generalization ability, indicating that the method is a competitive antenna design optimization strategy.