Adaptive arrangement classifier via neuro-fuzzy modeling

    研究成果: Conference contribution

    抄録

    A hybrid fuzzy-neuro classifier that extracts rules in terms of polyhedrons in the input space is proposed. The network uses a fuzzy disjunctive normal form in its hidden layer to effectively map polyhedral regions, which are gradually adjusted during learning, to category labels. The major advantage of the present method lies in that it is quite simple in architecture, every layer enjoys a clear fuzzy logical interpretation, and the number of rules needed is very few. The results of classification experiments seem to be quite promising.

    元の言語English
    ホスト出版物のタイトルIEEE International Conference on Fuzzy Systems
    出版場所Piscataway, NJ, United States
    出版者IEEE
    ページ577-580
    ページ数4
    2
    出版物ステータスPublished - 2000
    イベントFUZZ-IEEE 2000: 9th IEEE International Conference on Fuzzy Systems - San Antonio, TX, USA
    継続期間: 2000 5 72000 5 10

    Other

    OtherFUZZ-IEEE 2000: 9th IEEE International Conference on Fuzzy Systems
    San Antonio, TX, USA
    期間00/5/700/5/10

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    Experiments

    ASJC Scopus subject areas

    • Chemical Health and Safety
    • Software
    • Safety, Risk, Reliability and Quality

    これを引用

    Shiina, K. (2000). Adaptive arrangement classifier via neuro-fuzzy modeling. : IEEE International Conference on Fuzzy Systems (巻 2, pp. 577-580). Piscataway, NJ, United States: IEEE.

    Adaptive arrangement classifier via neuro-fuzzy modeling. / Shiina, Kempei.

    IEEE International Conference on Fuzzy Systems. 巻 2 Piscataway, NJ, United States : IEEE, 2000. p. 577-580.

    研究成果: Conference contribution

    Shiina, K 2000, Adaptive arrangement classifier via neuro-fuzzy modeling. : IEEE International Conference on Fuzzy Systems. 巻. 2, IEEE, Piscataway, NJ, United States, pp. 577-580, FUZZ-IEEE 2000: 9th IEEE International Conference on Fuzzy Systems, San Antonio, TX, USA, 00/5/7.
    Shiina K. Adaptive arrangement classifier via neuro-fuzzy modeling. : IEEE International Conference on Fuzzy Systems. 巻 2. Piscataway, NJ, United States: IEEE. 2000. p. 577-580
    Shiina, Kempei. / Adaptive arrangement classifier via neuro-fuzzy modeling. IEEE International Conference on Fuzzy Systems. 巻 2 Piscataway, NJ, United States : IEEE, 2000. pp. 577-580
    @inproceedings{d12f586e4bc64e089249e66f8d527258,
    title = "Adaptive arrangement classifier via neuro-fuzzy modeling",
    abstract = "A hybrid fuzzy-neuro classifier that extracts rules in terms of polyhedrons in the input space is proposed. The network uses a fuzzy disjunctive normal form in its hidden layer to effectively map polyhedral regions, which are gradually adjusted during learning, to category labels. The major advantage of the present method lies in that it is quite simple in architecture, every layer enjoys a clear fuzzy logical interpretation, and the number of rules needed is very few. The results of classification experiments seem to be quite promising.",
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