Genetic Algorithm: Application to Scattered Data Problems using Lipschitz Interpolation

Neil R. Garbacik, Dr. Mohammed A. Zohdy
{"title":"Genetic Algorithm: Application to Scattered Data Problems using Lipschitz Interpolation","authors":"Neil R. Garbacik, Dr. Mohammed A. Zohdy","doi":"10.1109/NAECON.2008.4806516","DOIUrl":null,"url":null,"abstract":"In this paper, a low computational method of efficiently and quickly handling large multivariate scattered data sets with a genetic algorithm for design parameter optimization is presented. The method presented combines the use of a genetic algorithm and the linear interpolation technique identified as Lipschitz Interpolation. Using this method we have improved the performance of the algorithm in two ways, the variance of the solution and the total algorithm evaluation time (an improvement of magnitude 90%).","PeriodicalId":254758,"journal":{"name":"2008 IEEE National Aerospace and Electronics Conference","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 IEEE National Aerospace and Electronics Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NAECON.2008.4806516","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

Abstract

In this paper, a low computational method of efficiently and quickly handling large multivariate scattered data sets with a genetic algorithm for design parameter optimization is presented. The method presented combines the use of a genetic algorithm and the linear interpolation technique identified as Lipschitz Interpolation. Using this method we have improved the performance of the algorithm in two ways, the variance of the solution and the total algorithm evaluation time (an improvement of magnitude 90%).
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
遗传算法:应用于使用Lipschitz插值的分散数据问题
本文提出了一种基于遗传算法的设计参数优化的低计算方法,可以高效、快速地处理大型多元分散数据集。该方法结合了遗传算法和线性插值技术,即利普希茨插值。使用该方法,我们从两个方面提高了算法的性能,即解的方差和算法的总评估时间(提高了90%)。
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
Modeling Protein-Based 3-D Memory in SPICE Image Registration using Polar Wavelets Untethered On-The-Fly Radio Assembly With Wires-On-Demand Integration of Vision based SLAM and Nonlinear Filter for Simple Mobile Robot Navigation Relative Track Metrics to Determine Model Mismatch
×
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