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3D fuzzy data approximation by fuzzy smoothing bicubic splines

Author

Listed:
  • González, P.
  • Idais, H.
  • Pasadas, M.
  • Yasin, M.

Abstract

Function approximation and interpolation are major and important problems in various scientific fields. In this work we present an approximation method of fuzzy data defined at a 3D fuzzy data set. We define a fuzzy smoothing bicubic spline approximation for a given fuzzy data set and we estimate the approximation error using similarity measures of fuzzy numbers. Examples are given to test the goodness of the method and compare the behavior of the indices proposed for different configurations of the fuzzy smoothing bicubic spline. Finally, some conclusions of the presented method are briefly discussed.

Suggested Citation

  • González, P. & Idais, H. & Pasadas, M. & Yasin, M., 2019. "3D fuzzy data approximation by fuzzy smoothing bicubic splines," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 164(C), pages 94-102.
    • Handle: RePEc:eee:matcom:v:164:y:2019:i:c:p:94-102
    DOI: 10.1016/j.matcom.2018.10.005
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    References listed on IDEAS

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    1. Merkus, H R & Pollock, D S G & de Vos, A F, 1993. "A Synopsis of the Smoothing Formulae Associated with the Kalman Filter," Computational Economics, Springer;Society for Computational Economics, vol. 6(3-4), pages 177-200, November.
    2. H.R. Merkus & D.S.G. Pollock & A.F. de Vos, 1991. "A Synopsis of the Smoothing Formulae Associated with the Kalman Filter," Working Papers 246, Queen Mary University of London, School of Economics and Finance.
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