Fuzzy autocorrelation model with confidence intervals of fuzzy random data

Yoshiyuki Yabuuchi, Junzo Watada

    研究成果: Conference contribution

    5 被引用数 (Scopus)

    抄録

    Economic analyses are typical methods based on time-series data or cross-section data. Economic systems are complex because they involve human behaviors and are affected by many factors. When a system includes such uncertainty, as those concerning human behaviors, a fuzzy system approach plays a pivotal role in such analysis. In this paper, we propose a fuzzy autocorrelation model with confidence intervals of fuzzy random time-series data. This confidence intervals has an essential role in dealing with fuzzy random data on our fuzzy autocorrelation model which we have presented. We analyze tick-by-tick data of stock dealing and compare two time-series models, a fuzzy autocorrelation model proposed by us, and a new fuzzy time-series model which we propose in this paper.

    本文言語English
    ホスト出版物のタイトル6th International Conference on Soft Computing and Intelligent Systems, and 13th International Symposium on Advanced Intelligence Systems, SCIS/ISIS 2012
    ページ1938-1943
    ページ数6
    DOI
    出版ステータスPublished - 2012
    イベント2012 Joint 6th International Conference on Soft Computing and Intelligent Systems, SCIS 2012 and 13th International Symposium on Advanced Intelligence Systems, ISIS 2012 - Kobe
    継続期間: 2012 11月 202012 11月 24

    Other

    Other2012 Joint 6th International Conference on Soft Computing and Intelligent Systems, SCIS 2012 and 13th International Symposium on Advanced Intelligence Systems, ISIS 2012
    CityKobe
    Period12/11/2012/11/24

    ASJC Scopus subject areas

    • 人工知能
    • ソフトウェア

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