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    Please use this identifier to cite or link to this item: http://nthur.lib.nthu.edu.tw/dspace/handle/987654321/46300

    Title: Pattern discovery from few data
    Authors: Wang, Hsiao-Fan
    教師: 王小璠
    Date: 2005
    Publisher: Institute of Electrical and Electronics Engineers
    Relation: Third International Conference on Information Technology and Applications, 2005. ICITA 2005, 4-7 July 2005, Volume 1, pages 284 - 287
    Keywords: Set Division
    Possibility Theory
    approximate membership function
    Abstract: Giving a limited data set, how to derive its properties is what we are interested in this study. Although because of the increasing power of computers and internet, collecting a huge number of data such that a database becomes a data warehouse is a common phenomenon, especially in industries, it cannot be denied that there were drastic disasters such as terrorist attacks, nuclear plants explosion which happened statistically few, yet resulted in incredible lost in many ways. How to analyze such data so that their patterns can be revealed and predicted is what we concerned. Based on Possibility Theory we have obtained some results that are reported in this paper with the discussion of its possible extension and applications.
    URI: http://www.ieee.org/
    Appears in Collections:[工業工程與工程管理學系] 會議論文

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