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Design and Optimization of Coplanar Capacitive Coupled Probe Fed MSA Using ANFIS

机译:利用ANFIS设计和优化共面电容耦合探头馈电MSA

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In this paper, an optimization method based on adaptive Neuro-Fuzzy inference system (ANFIS) for determining the parameters used in the design of a coplanar capacitive coupled probe fed rectangular microstrip antenna. The antenna was analyzed in the 2-10GHz range to demonstrate universal working of the proposed model. Here, an expert knowledge of fuzzy inference system (FIS) and the learning capability of artificial neural network (ANN) have been embedded (ANFIS). By calculating and optimizing the patch dimensions of a rectangular microstrip antenna with air gap, this paper shows that ANFIS produces good results that are in agreement with the mathematical analysis of the design parameters of antenna. Of the parameters considered for optimization, the error difference (average) between the proposed model and the calculated data is 0.21% for L, 0.41% for W, and 0.2% for air gap which are less than 0.5% and acceptably low.
机译:本文提出了一种基于自适应神经模糊推理系统(ANFIS)的优化方法,用于确定共面电容耦合探头馈送矩形微带天线设计中使用的参数。在2-10GHz范围内对天线进行了分析,以证明所提出模型的通用性。在此,已经嵌入了模糊推理系统(FIS)的专家知识和人工神经网络(ANN)的学习能力(ANFIS)。通过计算和优化带有气隙的矩形微带天线的贴片尺寸,本文表明ANFIS产生了与天线设计参数的数学分析一致的良好结果。在考虑优化的参数中,建议模型与计算数据之间的误差差(平均值)对于L为0.21%,对于W为0.41%,对于气隙为0.2%,这些误差小于0.5%并且可以接受。

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