时间数据的粒化:时间序列的全局视图

A. Bargiela, W. Pedrycz
{"title":"时间数据的粒化:时间序列的全局视图","authors":"A. Bargiela, W. Pedrycz","doi":"10.1109/NAFIPS.2003.1226780","DOIUrl":null,"url":null,"abstract":"In this paper we discuss the issue of granular representation of time series. The critical concern is the ability to capture the essential features of the time series in the abstract granular representation of it. The discussion uses a set-theoretical framework of fuzzy sets and employs the Fuzzy C-means algorithm for the evaluation of the information granules obtained in various ways.","PeriodicalId":153530,"journal":{"name":"22nd International Conference of the North American Fuzzy Information Processing Society, NAFIPS 2003","volume":"113 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2003-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"20","resultStr":"{\"title\":\"Granulation of temporal data: a global view on time series\",\"authors\":\"A. Bargiela, W. Pedrycz\",\"doi\":\"10.1109/NAFIPS.2003.1226780\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we discuss the issue of granular representation of time series. The critical concern is the ability to capture the essential features of the time series in the abstract granular representation of it. The discussion uses a set-theoretical framework of fuzzy sets and employs the Fuzzy C-means algorithm for the evaluation of the information granules obtained in various ways.\",\"PeriodicalId\":153530,\"journal\":{\"name\":\"22nd International Conference of the North American Fuzzy Information Processing Society, NAFIPS 2003\",\"volume\":\"113 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2003-07-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"20\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"22nd International Conference of the North American Fuzzy Information Processing Society, NAFIPS 2003\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NAFIPS.2003.1226780\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"22nd International Conference of the North American Fuzzy Information Processing Society, NAFIPS 2003","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NAFIPS.2003.1226780","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 20

摘要

本文讨论了时间序列的粒度表示问题。关键的问题是在抽象的粒度表示中捕捉时间序列的基本特征的能力。讨论使用模糊集的集合理论框架,并采用模糊c均值算法对各种方式获得的信息粒进行评价。
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
Granulation of temporal data: a global view on time series
In this paper we discuss the issue of granular representation of time series. The critical concern is the ability to capture the essential features of the time series in the abstract granular representation of it. The discussion uses a set-theoretical framework of fuzzy sets and employs the Fuzzy C-means algorithm for the evaluation of the information granules obtained in various ways.
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
Fuzzy-rough nearest-neighbor classification approach Fault detection and diagnosis in turbine engines using fuzzy logic How the number of measured dimensions affects fuzzy causal measures of vitamin therapy for hyperhomocysteinemia in stroke patients The fuzzy rough approximation decomposability Fuzzy-neuro system for bridge health monitoring
×
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