Fuzzy robust regression model by possibility maximization

Yoshiyuki Yabuuchi, Junzo Watada

    Research output: Contribution to journalArticle

    15 Citations (Scopus)

    Abstract

    Since management and economic systems are complex, it is hard to handle data obtained in management and economic areas. Hitherto, in the fields, much research has focused on the structure and analysis of such data. H. Tanaka et al. proposed a fuzzy regression model to illustrate the potential possibilities inherent in the target system. J. C. Bezdek proposed a switching regression model based on a fuzzy clustering model to separate mixed samples coming from plural latent systems and apply regression models to the groups of samples coming from each system. It is hard to illustrate a rough and moderate possibility of the target system. In this paper, to deal with the possibility of a social system, we propose a new fuzzy robust regression model.

    Original languageEnglish
    Pages (from-to)479-484
    Number of pages6
    JournalJournal of Advanced Computational Intelligence and Intelligent Informatics
    Volume15
    Issue number4
    Publication statusPublished - 2011 Jun

    Fingerprint

    Economics
    Fuzzy clustering

    Keywords

    • Fuzzy regression model
    • Possibility grade
    • Robustness

    ASJC Scopus subject areas

    • Artificial Intelligence
    • Computer Vision and Pattern Recognition
    • Human-Computer Interaction

    Cite this

    Fuzzy robust regression model by possibility maximization. / Yabuuchi, Yoshiyuki; Watada, Junzo.

    In: Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol. 15, No. 4, 06.2011, p. 479-484.

    Research output: Contribution to journalArticle

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