A pattern distance-based evolutionary approach to time series segmentation
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Yu, Jingwen | - |
dc.contributor.author | Yin, Jian | - |
dc.contributor.author | Zhou, Duanning | - |
dc.contributor.author | Zhang, Jun | - |
dc.date.accessioned | 2024-01-20T09:02:19Z | - |
dc.date.available | 2024-01-20T09:02:19Z | - |
dc.date.issued | 2006-08 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/117824 | - |
dc.description.abstract | Time series segmentation is a fundamental component in the process of analyzing and mining time series data. Given a set of pattern templates, evolutionary computation is an appropriate tool to segment time series flexibly and effectively. In this paper, we propose a new distance measure based on pattern distance for fitness evaluation. Time sequence is represented by a series of perceptually important points and converted into piecewise trend sequence. Pattern distance measures the trend similarity of two sequences. Moreovhttps://link.springer.com/chapter/10.1007/978-3-540-37256-1_99er, experiments are conducted to compare the performance of pattern-distance based method with the original one. Results show that pattern distance measure outperforms the original one in correct match, accurate segmentation. © Springer-Verlag Berlin/Heidelberg 2006. | - |
dc.format.extent | 6 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | Springer Verlag | - |
dc.title | A pattern distance-based evolutionary approach to time series segmentation | - |
dc.type | Article | - |
dc.publisher.location | 독일 | - |
dc.identifier.doi | 10.1007/11816492_99 | - |
dc.identifier.scopusid | 2-s2.0-33748985166 | - |
dc.identifier.wosid | 000240383400099 | - |
dc.identifier.bibliographicCitation | Intelligent Control and Automation International Conference on Intelligent Computing, ICIC 2006, Kunming, China, August, 2006, pp 797 - 802 | - |
dc.citation.title | Intelligent Control and Automation International Conference on Intelligent Computing, ICIC 2006, Kunming, China, August, 2006 | - |
dc.citation.startPage | 797 | - |
dc.citation.endPage | 802 | - |
dc.type.docType | Conference paper | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | sci | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Automation & Control Systems | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalWebOfScienceCategory | Automation & Control Systems | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Artificial Intelligence | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Information Systems | - |
dc.identifier.url | https://link.springer.com/chapter/10.1007/978-3-540-37256-1_99 | - |
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