CLC number: TP391.9; TN929.5
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 2022-06-02
Cited: 0
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Zhihao HE, Gang JIN, Yingjun WANG. A novel grey wolf optimizer and its applications in 5G frequency selection surface design[J]. Frontiers of Information Technology & Electronic Engineering,in press.https://doi.org/10.1631/FITEE.2100580 @article{title="A novel grey wolf optimizer and its applications in 5G frequency selection surface design", %0 Journal Article TY - JOUR
一种新型灰狼优化算法及其在5G频率选择表面设计中的应用1华南理工大学聚合物新型成型装备国家工程研究中心,中国广州市,510641 2华南理工大学聚合物成型加工工程教育部重点实验室,中国广州市,510641 3华南理工大学广东省高分子先进制造技术及装备重点实验室,中国广州市,510641 摘要:第五代无线通信系统(5G)的发展使元启发算法与电磁设备的设计过程结合得更为紧密。本文提出一种自适应灰狼优化器(SAGWO),并将其与一种基于单元节点的5G频率选择面(FSS)优化模型相结合。SAGWO包含3种改进策略:改进初始头狼的分配,增加随机探索能力和增强局部搜索能力,以加快收敛速度,有效避免局部最优。在基准函数测试中,SAGWO优于其他5种优化算法:原始灰狼优化器(GWO)、遗传算法(GA)、粒子群优化器(PSO)、改进灰狼优化算法(IGWO)和基于选择性对抗的灰狼优化算法(SOGWO)。因为SAGWO具有良好全局寻优能力,所以SAGWO适用于解决具有较大设计空间的5G FSS优化问题。将SAGWO与新的FSS优化模型相结合,能自动生成在中心工作频率处具有电磁屏蔽能力的FSS结构。为验证所提方法,本文设计了在28 GHz处具有电磁屏蔽能力的双层环形FSS。结果表明,优化后的FSS在中心频率处具有较好电磁干扰屏蔽能力和较高角稳定性。最后,制作并测试了优化后的FSS样品。 关键词组: Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article
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