{"title":"Genetic Algorithm and Particle Swarm Optimization Approach for Prediction of Physical Parameters of Rectangular-Shaped Microstrip Antenna","authors":"Zeynep Sidika Seven, S. Can","doi":"10.2339/politeknik.1194931","DOIUrl":null,"url":null,"abstract":"This study presents the results of two optimization algorithms for estimating the resonant frequency, bandwidth, feed point, and input impedance of a rectangular-shaped microstrip antenna. To minimize the design cost and design time, genetic algorithms and particle swarm optimization methods have been applied and compared. The antenna design parameters were considered by using a genetic algorithm (GA) and particle swarm optimization (PSO) is implemented in the MATLAB® environment. The calculation results were assimilated with other studies in the literature in terms of accuracy. The computational results of the optimized parameters are having a good agreement with the experimental results. The optimized antenna was modeled and verified by the analyses performed using the CST Studio Suite® software.","PeriodicalId":44937,"journal":{"name":"Journal of Polytechnic-Politeknik Dergisi","volume":" ","pages":""},"PeriodicalIF":0.4000,"publicationDate":"2023-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Polytechnic-Politeknik Dergisi","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2339/politeknik.1194931","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
This study presents the results of two optimization algorithms for estimating the resonant frequency, bandwidth, feed point, and input impedance of a rectangular-shaped microstrip antenna. To minimize the design cost and design time, genetic algorithms and particle swarm optimization methods have been applied and compared. The antenna design parameters were considered by using a genetic algorithm (GA) and particle swarm optimization (PSO) is implemented in the MATLAB® environment. The calculation results were assimilated with other studies in the literature in terms of accuracy. The computational results of the optimized parameters are having a good agreement with the experimental results. The optimized antenna was modeled and verified by the analyses performed using the CST Studio Suite® software.
本文研究了矩形微带天线的谐振频率、带宽、馈电点和输入阻抗的两种优化算法。为了使设计成本和设计时间最小化,对遗传算法和粒子群优化方法进行了比较。采用遗传算法(GA)和粒子群算法(PSO)对天线的设计参数进行了考虑。计算结果与文献中其他研究结果在准确性上基本一致。优化参数的计算结果与实验结果吻合较好。利用CST Studio Suite®软件对优化后的天线进行建模和分析验证。