改进的粒子群优化算法,便于硬件实现

M. Rajewski, Z. Dlugosz, R. Dlugosz, T. Talaśka
{"title":"改进的粒子群优化算法,便于硬件实现","authors":"M. Rajewski, Z. Dlugosz, R. Dlugosz, T. Talaśka","doi":"10.23919/MIXDES49814.2020.9155802","DOIUrl":null,"url":null,"abstract":"This paper presents various modifications and developments in the PSO algorithm. PSO is an algorithm based on the behavior of swarms. In this work we focus mainly on simplifying the algorithm by replacing random number generators, which can be a problem when implementing algorithms in hardware. We investigate how changing the methods for algorithm updates from random to more deterministic approach influences the results. This paper shows whether it is possible to achieve same as random or better results using a simplified algorithm, which uses simple mathematical operations in the algorithm optimization process.","PeriodicalId":145224,"journal":{"name":"2020 27th International Conference on Mixed Design of Integrated Circuits and System (MIXDES)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Modified Particle Swarm Optimization Algorithm Facilitating Its Hardware Implementation\",\"authors\":\"M. Rajewski, Z. Dlugosz, R. Dlugosz, T. Talaśka\",\"doi\":\"10.23919/MIXDES49814.2020.9155802\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents various modifications and developments in the PSO algorithm. PSO is an algorithm based on the behavior of swarms. In this work we focus mainly on simplifying the algorithm by replacing random number generators, which can be a problem when implementing algorithms in hardware. We investigate how changing the methods for algorithm updates from random to more deterministic approach influences the results. This paper shows whether it is possible to achieve same as random or better results using a simplified algorithm, which uses simple mathematical operations in the algorithm optimization process.\",\"PeriodicalId\":145224,\"journal\":{\"name\":\"2020 27th International Conference on Mixed Design of Integrated Circuits and System (MIXDES)\",\"volume\":\"15 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 27th International Conference on Mixed Design of Integrated Circuits and System (MIXDES)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23919/MIXDES49814.2020.9155802\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 27th International Conference on Mixed Design of Integrated Circuits and System (MIXDES)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/MIXDES49814.2020.9155802","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

本文介绍了粒子群算法的各种改进和发展。粒子群优化算法是一种基于群体行为的算法。在这项工作中,我们主要关注通过替换随机数生成器来简化算法,这在硬件中实现算法时可能是一个问题。我们研究了将算法更新的方法从随机方法更改为更确定的方法如何影响结果。本文展示了在算法优化过程中使用简单数学运算的简化算法是否有可能达到与随机相同或更好的结果。
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
Modified Particle Swarm Optimization Algorithm Facilitating Its Hardware Implementation
This paper presents various modifications and developments in the PSO algorithm. PSO is an algorithm based on the behavior of swarms. In this work we focus mainly on simplifying the algorithm by replacing random number generators, which can be a problem when implementing algorithms in hardware. We investigate how changing the methods for algorithm updates from random to more deterministic approach influences the results. This paper shows whether it is possible to achieve same as random or better results using a simplified algorithm, which uses simple mathematical operations in the algorithm optimization process.
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
Combining ε-similar Fuzzy Rules for Efficient Classification of Cardiotocographic Signals Design of Integrated Circuits and Microsystems Comparison of Set-ups Dedicated to Measure Thermal Parameters of Power LEDs Parameter Extraction for a Simplified EKV-model in a 28nm FDSOI Technology 1MHz Gate Driver in Power Technology for Fast Switching Applications
×
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