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Quantitative Measurement for Fuzzy System to Input and Rule Perturbations

  • Conference paper
  • First Online:
Computational Intelligence (ICIC 2006)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4114))

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Abstract

In practice, input and rule perturbation are two important factors that will heavily influence the performance of fuzzy system. Quantitatively measure the influence of these two kinds of perturbation on the input/output mapping relationship of fuzzy system has great significance, theoretically and practically. In this paper, a statistical-based quantitative measurement for input and rule perturbation is proposed. By using the proposed approach, influence of perturbations on fuzzy system can be computed quantitatively, analytically and efficiently. Simulation results demonstrate the effectiveness of the proposed approach.

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Authors and Affiliations

  1. School of Computer Science and Technology, Nanjing University of Science and Technology, Nanjing, 210094, China

    Dong-Jun Yu & Jing-Yu Yang

  2. School of Computer Science and Technology, Jiangsu University of Science and Technology, Zhenjiang, 212003, China

    Xiao-Jun Wu

Authors
  1. Dong-Jun Yu
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  2. Xiao-Jun Wu
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  3. Jing-Yu Yang
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Editor information

Editors and Affiliations

  1. Institute of Intelligent Machines , Chinese Academy of Sciences , Anhui, Hefei, China

    De-Shuang Huang

  2. Queen’s University , Belfast, UK

    Kang Li  & George William Irwin  & 

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© 2006 Springer-Verlag Berlin Heidelberg

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Yu, DJ., Wu, XJ., Yang, JY. (2006). Quantitative Measurement for Fuzzy System to Input and Rule Perturbations. In: Huang, DS., Li, K., Irwin, G.W. (eds) Computational Intelligence. ICIC 2006. Lecture Notes in Computer Science(), vol 4114. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-37275-2_21

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  • DOI: https://doi.org/10.1007/978-3-540-37275-2_21

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-37274-5

  • Online ISBN: 978-3-540-37275-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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