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Fuzzy linguistic model for interpolation

Author

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  • Abbasbandy, S.
  • Adabitabar Firozja, M.

Abstract

In this paper, a fuzzy method for interpolating of smooth curves was represented. We present a novel approach to interpolate real data by applying the universal approximation method. In proposed method, fuzzy linguistic model (FLM) applied as universal approximation for any nonlinear continuous function. Finally, we give some numerical examples and compare the proposed method with spline method.

Suggested Citation

  • Abbasbandy, S. & Adabitabar Firozja, M., 2007. "Fuzzy linguistic model for interpolation," Chaos, Solitons & Fractals, Elsevier, vol. 34(2), pages 551-556.
    • Handle: RePEc:eee:chsofr:v:34:y:2007:i:2:p:551-556
    DOI: 10.1016/j.chaos.2006.03.102
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    References listed on IDEAS

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    1. Abbasbandy, S. & Nieto, Juan J. & Alavi, M., 2005. "Tuning of reachable set in one dimensional fuzzy differential inclusions," Chaos, Solitons & Fractals, Elsevier, vol. 26(5), pages 1337-1341.
    2. Tanaka, Yosuke & Mizuno, Yuzi & Kado, Tatsuhiko, 2005. "Chaotic dynamics in the Friedmann equation," Chaos, Solitons & Fractals, Elsevier, vol. 24(2), pages 407-422.
    3. Jiang, Wang & Guo-Dong, Qiao & Bin, Deng, 2005. "H∞ Variable universe adaptive fuzzy control for chaotic system," Chaos, Solitons & Fractals, Elsevier, vol. 24(4), pages 1075-1086.
    4. Caldas, M. & Jafari, S., 2005. "θ-Compact fuzzy topological spaces," Chaos, Solitons & Fractals, Elsevier, vol. 25(1), pages 229-232.
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