Optimization Method of Microwave Devices Based on Improved Extreme Learning Machine

Author:

Hu Cong,Chen Yuanxiang,Sun Shangbin,Fu Jia,Yu Jianguo

Abstract

Abstract With the rapid development of modern wireless technology, it is necessary to continuously optimize microwave devices to meet the higher requirements of communication systems. In this paper, we propose a microwave device optimization method based on extreme learning machine (ELM) and gray wolf optimizer (GWO). we adopt GWO to optimize the parameters of ELM and establish the mapping relationships between the microwave device design parameters and their responses. According to the inverse mapping of expected response, the expected design parameters of microwave devices are obtained. The numerical results show that the proposed method can improve the design efficiency of microwave devices and realize automatic optimization design compared with the existing method.

Publisher

IOP Publishing

Subject

General Physics and Astronomy

Reference12 articles.

1. Computational Optimization Algorithms for Antennas and RF/Microwave Circuit Designs: An Overview;Yeung;IEEE Transactions on Industrial Informatics,2012

2. Design and optimization of large conversion gain active microwave frequency triplers;Johnson;IEEE Microwave and Wireless Components Letters,2005

3. Comparative Study of Optimization Algorithms on the Design of Broadband Antennas;Kovaleva;IEEE Journal on Multiscale and Multiphysics Computational Techniques,2020

4. Adaptive Feature Zero Assisted Surrogate-Based EM Optimization for Microwave Filter Design;Feng;IEEE Microwave and Wireless Components Letters,2019

5. Global Optimization of Microwave Filters Based on a Surrogate Model-Assisted Evolutionary Algorithm;Liu;IEEE Transactions on Microwave Theory and Techniques,2017

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3