Abdelaziz A. Abdelhamid1,3,*, Sultan R. Alotaibi2
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 917-933, 2022, DOI:10.32604/cmc.2022.027653
Abstract Employing machine learning techniques in predicting the parameters of metamaterial antennas has a significant impact on the reduction of the time needed to design an antenna with optimal parameters using simulation tools. In this paper, we propose a new approach for predicting the bandwidth of metamaterial antenna using a novel ensemble model. The proposed ensemble model is composed of two levels of regression models. The first level consists of three strong models namely, random forest, support vector regression, and light gradient boosting machine. Whereas the second level is based on the ElasticNet regression model, which receives the prediction results from… More >
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