非线性pso收敛分析及参数调整方案

2010 IEEE Fifth International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA) Pub Date : 2010-11-29 DOI:10.1109/BICTA.2010.5645105

Xuexue Zhao, Gang-lin Wang

{"title":"非线性pso收敛分析及参数调整方案","authors":"Xuexue Zhao, Gang-lin Wang","doi":"10.1109/BICTA.2010.5645105","DOIUrl":null,"url":null,"abstract":"Linear parameter adjustment (LP A) schemes had been widely used in particle swarm optimization (PSO). In this paper, we develop a novel PSO algorithm with nonlinear parameter adjustment (NLP A) called nonlinear PSO and present its convergence analysis. Simulations on five standard test functions confirm the validity of the nonlinear parameter adjustment methods.","PeriodicalId":302619,"journal":{"name":"2010 IEEE Fifth International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Nonlinear PSO—Convergence analysis and parameter adjustment schemes\",\"authors\":\"Xuexue Zhao, Gang-lin Wang\",\"doi\":\"10.1109/BICTA.2010.5645105\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Linear parameter adjustment (LP A) schemes had been widely used in particle swarm optimization (PSO). In this paper, we develop a novel PSO algorithm with nonlinear parameter adjustment (NLP A) called nonlinear PSO and present its convergence analysis. Simulations on five standard test functions confirm the validity of the nonlinear parameter adjustment methods.\",\"PeriodicalId\":302619,\"journal\":{\"name\":\"2010 IEEE Fifth International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA)\",\"volume\":\"22 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-11-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 IEEE Fifth International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/BICTA.2010.5645105\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE Fifth International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BICTA.2010.5645105","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 2

摘要

线性参数平差(LP A)方法在粒子群优化(PSO)中得到广泛应用。本文提出了一种具有非线性参数调整(NLP a)的新型粒子群算法——非线性粒子群算法，并给出了其收敛性分析。通过对5种标准测试函数的仿真，验证了非线性参数调整方法的有效性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Nonlinear PSO—Convergence analysis and parameter adjustment schemes

Linear parameter adjustment (LP A) schemes had been widely used in particle swarm optimization (PSO). In this paper, we develop a novel PSO algorithm with nonlinear parameter adjustment (NLP A) called nonlinear PSO and present its convergence analysis. Simulations on five standard test functions confirm the validity of the nonlinear parameter adjustment methods.

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

2010 IEEE Fifth International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA)

自引率

0.00%

发文量