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A neuro-fuzzy architecture for high performance classification

  • Fuzzy — Neural Networks
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Advances in Fuzzy Logic, Neural Networks and Genetic Algorithms (WWW 1994)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1011))

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Abstract

The concept of combining modular neural networks has been recently exploited as a new direction for the development of highly reliable neural network systems in the area of pattern classification. In this paper we present an efficient method for combining the modular networks based on fuzzy logic, especially the fuzzy integral. This method nonlinearly combines objective evidences, in the form of network outputs, with subjective evaluation of the reliability of the individual neural networks. Also, for more effective aggregation, we adopt the extension of the fuzzy integral with ordered weighted averaging operators. The experimental results with the recognition problem of on-line handwriting characters show that the performance of individual networks could be improved significantly.

This work was partly conducted while at: KAIST Computer Science Department, 373-1 Koosung-dong, Yoosung-ku, Taejeon 305–701, Korea, sbchogorai.kaist.ac.kr; and ATR Human Information Processing Research Laboratories, 2-2 Hikaridai, Seika-cho, Soraku-gun, Kyoto 619-02, Japan, sbchohip.atr.co.jp

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Authors and Affiliations

  1. Department of Computer Science, Yonsei University, 134 Shinchon-dong, 120-749, Sudaemoon-ku, Seoul, Korea

    Sung-Bae Cho

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  1. Sung-Bae Cho
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Takeshi Furuhashi

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© 1995 Springer-Verlag Berlin Heidelberg

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Cho, SB. (1995). A neuro-fuzzy architecture for high performance classification. In: Furuhashi, T. (eds) Advances in Fuzzy Logic, Neural Networks and Genetic Algorithms. WWW 1994. Lecture Notes in Computer Science, vol 1011. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-60607-6_6

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  • DOI: https://doi.org/10.1007/3-540-60607-6_6

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-60607-9

  • Online ISBN: 978-3-540-48457-8

  • eBook Packages: Springer Book Archive

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