English  |  正體中文  |  简体中文  |  全文笔数/总笔数 : 52310/87426 (60%)
造访人次 : 9085107      在线人数 : 292
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
搜寻范围 查询小技巧:
  • 您可在西文检索词汇前后加上"双引号",以获取较精准的检索结果
  • 若欲以作者姓名搜寻,建议至进阶搜寻限定作者字段,可获得较完整数据
  • 进阶搜寻


    jsp.display-item.identifier=請使用永久網址來引用或連結此文件: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/107914


    题名: A GA-based approach for finding appropriate granularity levels of patterns from time series
    作者: Chen, Chun-Hao;Tseng, Vincent S.;Yu, Hsieh-Hui;Hong, Tzung-Pei;Yen, Neil Y.
    日期: 2016-01
    上传时间: 2016-10-18 02:10:22 (UTC+8)
    出版者: Inderscience Publishers
    摘要: In our previous approach, we proposed an algorithm for finding segments and patterns simultaneously from a given time series. In that approach, because patterns were derived through clustering techniques, the number of clusters was hard to be setting. In other words, the granularity of derived patterns was not taken into consideration. Hence, an approach for deriving appropriate granularity levels of patterns is proposed in this paper. The cut points of a time series are first encoded into a chromosome. Each two adjacent cut points represents a segment. The segments in a chromosome are then divided into groups using the cluster affinity search technique with a similarity matrix and an affinity threshold. With the affinity threshold, patterns with the desired granularity level can be derived. Experiments on a real dataset are also conducted to demonstrate the effectiveness of the proposed approach.
    關聯: International Journal of Web and Grid Services 12(3), pp.217 - 239
    DOI: 10.1504/IJWGS.2016.079159
    显示于类别:[資訊工程學系暨研究所] 期刊論文

    文件中的档案:

    档案 描述 大小格式浏览次数
    index.html0KbHTML119检视/开启

    在機構典藏中所有的数据项都受到原著作权保护.

    TAIR相关文章

    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - 回馈