Application of Particle Swarm Optimization to Seismic Location

Dong-xue Han, Gai-yun Wang
{"title":"Application of Particle Swarm Optimization to Seismic Location","authors":"Dong-xue Han, Gai-yun Wang","doi":"10.1109/WGEC.2009.48","DOIUrl":null,"url":null,"abstract":"The particle swarm optimization (PSO) is an adaptive optimization based on swarm intelligence. The basic principle and the method of it being used in seismic location were introduced. To get a more accurate result, the objective function is the residual square sum of the observational travel-time and theoretical travel-time of the same earthquake return two stations. Compared with Genetic Algorithm on Seismic Location, PSO, after numerous experiments, proved its distinct superiority to locate the hypocenter more quickly and accurately. PSO is potentially useful for seismic location.","PeriodicalId":277950,"journal":{"name":"2009 Third International Conference on Genetic and Evolutionary Computing","volume":"85 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 Third International Conference on Genetic and Evolutionary Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WGEC.2009.48","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

Abstract

The particle swarm optimization (PSO) is an adaptive optimization based on swarm intelligence. The basic principle and the method of it being used in seismic location were introduced. To get a more accurate result, the objective function is the residual square sum of the observational travel-time and theoretical travel-time of the same earthquake return two stations. Compared with Genetic Algorithm on Seismic Location, PSO, after numerous experiments, proved its distinct superiority to locate the hypocenter more quickly and accurately. PSO is potentially useful for seismic location.
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
粒子群算法在地震定位中的应用
粒子群算法是一种基于群体智能的自适应优化算法。介绍了它在地震定位中的基本原理和方法。为了得到更准确的结果,目标函数为同一地震回波两个台站的观测走时与理论走时的残差平方和。与遗传算法在地震定位中的应用相比,粒子群算法在快速准确定位震源方面具有明显的优势。PSO可能对地震定位有用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
A Method of Robust Stabilization for the Delay Neural Networks with Nonlinear Perturbations A New Association Rules Mining Algorithm Based on Vector Research on Multidisciplinary Design Optimization Based Response Surface Technology of Artificial Neural Network Chaotic Analysis of Seismic Time Series and Short-Term Prediction with RBF Neural Networks An Optimization Approach of Ant Colony Algorithm and Adaptive Genetic Algorithm for MCM Interconnect Test
×
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