Clustering Analysis Based Modeling Method of Bridge State Anomaly Distribution

Lim Ji, Huo Lin, T. Hong, Han Zhongtao
{"title":"Clustering Analysis Based Modeling Method of Bridge State Anomaly Distribution","authors":"Lim Ji, Huo Lin, T. Hong, Han Zhongtao","doi":"10.1109/IICSPI.2018.8690391","DOIUrl":null,"url":null,"abstract":"Based on the measured data of bridges, this paper uses the clustering method of data-driven methods to analyze the abnormal state of bridges from the perspective of data. Two commonly used clustering algorithms are summarized here: Kmeans clustering algorithm and fuzzy C-means clustering algorithm. The theory and concrete operation steps of the respective methods are systematically discussed, and the advantages and disadvantages of the respective algorithms are compared.","PeriodicalId":6673,"journal":{"name":"2018 IEEE International Conference of Safety Produce Informatization (IICSPI)","volume":"22 1","pages":"292-295"},"PeriodicalIF":0.0000,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE International Conference of Safety Produce Informatization (IICSPI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IICSPI.2018.8690391","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Based on the measured data of bridges, this paper uses the clustering method of data-driven methods to analyze the abnormal state of bridges from the perspective of data. Two commonly used clustering algorithms are summarized here: Kmeans clustering algorithm and fuzzy C-means clustering algorithm. The theory and concrete operation steps of the respective methods are systematically discussed, and the advantages and disadvantages of the respective algorithms are compared.
基于聚类分析的桥梁状态异常分布建模方法
本文以桥梁实测数据为基础,采用数据驱动方法中的聚类方法,从数据的角度对桥梁异常状态进行分析。本文总结了两种常用的聚类算法:Kmeans聚类算法和模糊c均值聚类算法。系统地讨论了各种方法的理论和具体操作步骤,并比较了各种算法的优缺点。
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 求助全文
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信