自适应克隆免疫算法应用于宽带匹配网络设计

李文涛; 郭玉春; 史小卫

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自适应克隆免疫算法应用于宽带匹配网络设计

更新时间：2026-09-14

- 自适应克隆免疫算法应用于宽带匹配网络设计
- 自适应克隆免疫算法应用于宽带匹配网络设计
- Issue 3, (2010)
- 作者机构：
  
  西安电子科技大学天线与微波技术国家重点实验室
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2010
- 稿件说明：
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李文涛, 郭玉春, 史小卫. 自适应克隆免疫算法应用于宽带匹配网络设计[J]. 2010, (3).
DOI：

李文涛, 郭玉春, 史小卫. 自适应克隆免疫算法应用于宽带匹配网络设计[J]. 2010, (3). DOI：

摘要

针对克隆选择算法的不足

提出了一种自适应克隆免疫算法.直接根据抗体的多样性来确定克隆规模

通过引入抗体的自适应变异操作

增加对精英抗体的记忆和相似抑制操作来产生种群新个体

以保证算法的全局收敛性和抗体的多样性.将该算法应用于宽带匹配网络的拓扑结构和元件值的综合优化设计中

并分析了优化过程中频率采样点数的合理选取问题.仿真结果通过与实频法、遗传算法和克隆选择算法相比较

表明该算法具有更快的收敛速度

设计的匹配网络具有更优的匹配性能.

Abstract

Due to the shortage of clonal selection algorithm

an adaptive clonal immune algorithm(ACIA) was presented.The number of clones was directly determined by the diversity of antibodies.To generate population new individual

the adaptive mutation operation and integrated resemble restrain strategy with the memory for elites operation were adopted to ensure the global convergence of the algorithm and the diversity of the antibodies.In the process of optimizing the topology and element parameters of broadband matching network

the amount of sampled frequency in the optimization was analyzed.By comparison with the real frequency method

genetic algorithm and clonal selection algorithm

simulation results demonstrate that the proposed algorithm shows better performance and faster convergence speed.

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