Peng-Fei Qin, Wen-Hao Li, Dong Wang, Guanhua Huang, W. Fan, C. Sim
{"title":"A Linear Decreasing Inertia Weight Particle Swarm Optimization Base on a $K$-means Clustering Chaotic Sampling for Antenna Design","authors":"Peng-Fei Qin, Wen-Hao Li, Dong Wang, Guanhua Huang, W. Fan, C. Sim","doi":"10.1109/CSRSWTC56224.2022.10098311","DOIUrl":null,"url":null,"abstract":"This paper presents a $K$-means clustering chaotic sampling linear decreasing inertia weight particle swarm optimization (KCS-LDIWPSO) method for antenna fast design application. In this proposed method, a $K$-means clustering chaotic sampling method is used to obtain the initial particle swarm. The linear decreasing inertia weight particle swarm optimization method updates the particles to improve the optimization capability of the particle swarm optimization method. The proposed method is verified through optimization of a slotted patch antenna. The results show that the proposed method finds a required antenna with less simulation cost and computational time than other optimization methods.","PeriodicalId":198168,"journal":{"name":"2022 Cross Strait Radio Science & Wireless Technology Conference (CSRSWTC)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 Cross Strait Radio Science & Wireless Technology Conference (CSRSWTC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSRSWTC56224.2022.10098311","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
This paper presents a $K$-means clustering chaotic sampling linear decreasing inertia weight particle swarm optimization (KCS-LDIWPSO) method for antenna fast design application. In this proposed method, a $K$-means clustering chaotic sampling method is used to obtain the initial particle swarm. The linear decreasing inertia weight particle swarm optimization method updates the particles to improve the optimization capability of the particle swarm optimization method. The proposed method is verified through optimization of a slotted patch antenna. The results show that the proposed method finds a required antenna with less simulation cost and computational time than other optimization methods.