基于Rao和Jaya算法的线性天线阵列合成

Nagavalli Vegesna, G. Yamuna, T. S. Kumar
{"title":"基于Rao和Jaya算法的线性天线阵列合成","authors":"Nagavalli Vegesna, G. Yamuna, T. S. Kumar","doi":"10.3233/kes-220001","DOIUrl":null,"url":null,"abstract":"Optimization algorithms are being widely applied in real-time applications. In recent times, Jaya and Rao algorithms have been prominent. The performance of these algorithms will be analyzed for the objective function. The results thus obtained are more accurate and fast compared to previous algorithms. Also, Jaya and Rao algorithms will be utilized for linear array antenna synthesis for the arrays that are equally spaced. Therefore it is of present interest to evaluate the performance of linear antenna array using these algorithms.","PeriodicalId":210048,"journal":{"name":"Int. J. Knowl. Based Intell. Eng. Syst.","volume":"2012 31","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Linear Antenna Array synthesis using Rao and Jaya algorithms\",\"authors\":\"Nagavalli Vegesna, G. Yamuna, T. S. Kumar\",\"doi\":\"10.3233/kes-220001\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Optimization algorithms are being widely applied in real-time applications. In recent times, Jaya and Rao algorithms have been prominent. The performance of these algorithms will be analyzed for the objective function. The results thus obtained are more accurate and fast compared to previous algorithms. Also, Jaya and Rao algorithms will be utilized for linear array antenna synthesis for the arrays that are equally spaced. Therefore it is of present interest to evaluate the performance of linear antenna array using these algorithms.\",\"PeriodicalId\":210048,\"journal\":{\"name\":\"Int. J. Knowl. Based Intell. Eng. Syst.\",\"volume\":\"2012 31\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-06-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Int. J. Knowl. Based Intell. Eng. Syst.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3233/kes-220001\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Knowl. Based Intell. Eng. Syst.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3233/kes-220001","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

优化算法在实时应用中得到了广泛的应用。近年来,Jaya和Rao算法一直很突出。本文将以目标函数分析这些算法的性能。与以往的算法相比,得到的结果更加准确和快速。此外,Jaya和Rao算法将用于等间距阵列的线阵天线合成。因此,利用这些算法来评估线性天线阵列的性能是目前的研究热点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Linear Antenna Array synthesis using Rao and Jaya algorithms
Optimization algorithms are being widely applied in real-time applications. In recent times, Jaya and Rao algorithms have been prominent. The performance of these algorithms will be analyzed for the objective function. The results thus obtained are more accurate and fast compared to previous algorithms. Also, Jaya and Rao algorithms will be utilized for linear array antenna synthesis for the arrays that are equally spaced. Therefore it is of present interest to evaluate the performance of linear antenna array using these algorithms.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
DICO: Dingo coot optimization-based ZF net for pansharpening Hybrid modified weighted water cycle algorithm and Deep Analytic Network for forecasting and trend detection of forex market indices Autonomous gesture recognition using multi-layer LSTM networks and laban movement analysis KinRob: An ontology based robot for solving kinematic problems Machine learning approach for corona virus disease extrapolation: A case study
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1