Analysis using rough set of time series data including a large variation

Yoshiyuki Matsumoto, Junzo Watada

    研究成果: Conference contribution

    抄録

    Rough set theory was proposed by Z. Pawlak in 1982. This theory can mine knowledge granules through a decision rule from a database, a web base, a set and so on. The decision rule is used for data analysis as well. And we can apply the decision rule to reason, estimate, evaluate, or forecast an unknown object. In this paper, the rough set theory is used to analysis of time series data. Knowledge granules are minded from the data set of tick-wise price fluctuations. We acquire knowledge from the time-series data including large variation. And we compare the data including large variation and normal data.

    本文言語English
    ホスト出版物のタイトル2014 Joint 7th International Conference on Soft Computing and Intelligent Systems, SCIS 2014 and 15th International Symposium on Advanced Intelligent Systems, ISIS 2014
    出版社Institute of Electrical and Electronics Engineers Inc.
    ページ1378-1381
    ページ数4
    ISBN(印刷版)9781479959556
    DOI
    出版ステータスPublished - 2014 2 18
    イベント2014 Joint 7th International Conference on Soft Computing and Intelligent Systems, SCIS 2014 and 15th International Symposium on Advanced Intelligent Systems, ISIS 2014 - Kitakyushu, Japan
    継続期間: 2014 12 32014 12 6

    Other

    Other2014 Joint 7th International Conference on Soft Computing and Intelligent Systems, SCIS 2014 and 15th International Symposium on Advanced Intelligent Systems, ISIS 2014
    CountryJapan
    CityKitakyushu
    Period14/12/314/12/6

    ASJC Scopus subject areas

    • Software
    • Artificial Intelligence

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