基于RBFNN和GA优化设计DGS微带线

采用神经网络与遗传算法相结合的方法，对一种缺陷接地结构微带线进行优化设计。整个优化设计过程分为两步进行：首先采用基于混合递阶遗传算法优化训练的RBF神经网络对缺陷接地结构微带线进行建模，当神经网络模型训练成功后就实现了对这种缺陷地结构微带线传输系数快速和精确的输出仿真；然后利用该神经网络模型，并结合遗传算法共同优化设计这种缺陷地结构微带线的传输系数和尺寸参数。仿真结果验证了该方法的有效性和准确性。

Design and Optimization of DGS Microstrip Based on RBFNN and GA

The RBF neural network and genetic algorithms are successfully applied to the design and optimization of a DGS microstrip.The design and optimization procedure can be divided into two steps.Firstly,this RBF neural network based on hybrid hierarchy genetic algorithms is applied to the modeling of the DGS microstrip,and the transmission coefficient of the DGS microstrip can be obtained from the neural network model which is trained successfully.Secondly,according to the design goal,the transmission coefficien...