Building a type II fuzzy qualitative regression model

Yicheng Wei, Junzo Watada

    研究成果: Chapter

    9 被引用数 (Scopus)

    抄録

    The qualitative regression analysis models quantitatively change in the qualitative object variables by using qualitative values of multivariate data (membership degree or type I fuzzy set), which are given by subjective recognitions and judgments. From fuzzy set-theoretical points of view, uncertainty also exists when associated with the membership function of a type I fuzzy set. It will have much impact on the fuzziness of the qualitative objective external criterion. This paper is trying to model the qualitative change of external criterion's fuzziness by applying type II fuzzy set (we will use type II fuzzy set as well as type II fuzzy data in this paper). Here, qualitative values are assumed to be fuzzy degree of membership in qualitative categories and qualitative change in the objective external criterion is given as the fuzziness of the output.

    本文言語English
    ホスト出版物のタイトルSmart Innovation, Systems and Technologies
    ページ145-154
    ページ数10
    15
    DOI
    出版ステータスPublished - 2012

    出版物シリーズ

    名前Smart Innovation, Systems and Technologies
    15
    ISSN(印刷版)21903018
    ISSN(電子版)21903026

    ASJC Scopus subject areas

    • Computer Science(all)
    • Decision Sciences(all)

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