Design of circularly-polarized microstrip antenna by SVM ensemble
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Graphical Abstract
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Abstract
A large deal of calculating data and complex structure is needed when design circularly-polarized microstrip antenna (CPMSA) with artificial neural network. To solve this problem, a synthesis model based on SVM ensemble (SVME) is proposed for the design of single-feed CPSMA with truncated corners. This method was based on the features of high fitting precision, simple structure, and the strong generalization ability of the support vector machine (SVM). The basic idea of the method was to optimally select differential SVMs to construct SVME with the aid of binary particle swarm optimization (BiPSO) algorithm. The model is validated by comparing its results with artificial neural network and a single SVM. Experiments show that the method is effective. It may improve the generalization ability of SVM and reduce the prediction error, and this model is superior to the problem of existing conclusions.
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