Study on Parameter Distribution in Structure Reliability Analysis: Machine Learning Algorithm and Application

Y. Wan, Yangu Zhang
{"title":"Study on Parameter Distribution in Structure Reliability Analysis: Machine Learning Algorithm and Application","authors":"Y. Wan, Yangu Zhang","doi":"10.1109/WKDD.2009.169","DOIUrl":null,"url":null,"abstract":"The discrimination of parameter probability distribution type is the key to structure reliability analysis. A support vector machine (SVM) intelligent recognition model of probability distribution law is presented aiming at traditional method disadvantage. The intelligent recognition model of probability distribution is constructed by SVM algorithm realization, network design and feature extraction, inward stress probability distribution type of a stem structural member is recognized by the model, recognition result is Weibull distribution, SVM has a good generalization ability and clustering ability by comparison between network recognition result and regression analysis, the experiment result shows total recognition rate achieved 98.25%, it provides a good new method for structure reliability analysis.","PeriodicalId":143250,"journal":{"name":"2009 Second International Workshop on Knowledge Discovery and Data Mining","volume":"75 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 Second International Workshop on Knowledge Discovery and Data Mining","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WKDD.2009.169","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

The discrimination of parameter probability distribution type is the key to structure reliability analysis. A support vector machine (SVM) intelligent recognition model of probability distribution law is presented aiming at traditional method disadvantage. The intelligent recognition model of probability distribution is constructed by SVM algorithm realization, network design and feature extraction, inward stress probability distribution type of a stem structural member is recognized by the model, recognition result is Weibull distribution, SVM has a good generalization ability and clustering ability by comparison between network recognition result and regression analysis, the experiment result shows total recognition rate achieved 98.25%, it provides a good new method for structure reliability analysis.
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
结构可靠性分析中的参数分布研究:机器学习算法及其应用
参数概率分布类型的判别是结构可靠度分析的关键。针对传统方法的不足,提出了一种基于概率分布规律的支持向量机智能识别模型。通过SVM算法实现、网络设计和特征提取,构建了概率分布的智能识别模型,通过模型识别出某茎结构构件的向内应力概率分布类型,识别结果为威布尔分布,通过网络识别结果与回归分析的对比,SVM具有良好的概化能力和聚类能力,实验结果表明总识别率达到98.25%。为结构可靠度分析提供了一种新的方法。
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 Novel Blind Watermarking Scheme in Contourlet Domain Based on Singular Value Decomposition Research on the Electric Power Enterprise Performance Evaluation Based on Symbiosis Theory Structured Topology for Trust in P2P Network Prediction by Integration of Phase Space Reconstruction and a Novel Evolutionary System under Deregulated Power Market Weak Signal Detection Based on Chaotic Prediction
×
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