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Fitting of Fuzzy Fractal Interpolation for Uncertain Data

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Information and Automation (ISIA 2010)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 86))

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Abstract

Tackling of uncertain data is a major problem in data analysis and processing. The fuzzy theory with fuzzy numbers and fractal interpolation is employed to solve the issue of uncertainty. Sample data is used as the kernel of Gaussian fuzzy membership function and its fuzzy numbers are obtained by specifying λ-cut. These fuzzy numbers are used as uncertain data and defined as a new kind of fuzzy interpolation points. With these interpolation points fractal interpolation method is applied to fit curve of sample data. By these definitions, the flow of interpolation approach is given, and example is illustrated to show that a novel interpolation scheme is proposed for manipulating uncertain data.

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Author information

Authors and Affiliations

  1. Engineering and Technology Center, Southwest University of Science and Technology, Mianyang, 621010, Sichuan, China

    Xiaoping Xiao & Shiliang Yan

  2. School of Manufacturing Science and Engineering, Southwest University of Science and Technology, Mianyang, 621010, Sichuan, China

    Zisheng Li

Authors
  1. Xiaoping Xiao
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  2. Zisheng Li
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  3. Shiliang Yan
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Editor information

Editors and Affiliations

  1. Wuhan Institute of Technology, Wuhan, Hubei, China

    Luo Qi

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© 2011 Springer-Verlag Berlin Heidelberg

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Xiao, X., Li, Z., Yan, S. (2011). Fitting of Fuzzy Fractal Interpolation for Uncertain Data. In: Qi, L. (eds) Information and Automation. ISIA 2010. Communications in Computer and Information Science, vol 86. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19853-3_11

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  • DOI: https://doi.org/10.1007/978-3-642-19853-3_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-19852-6

  • Online ISBN: 978-3-642-19853-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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