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Efficient Simple Large Scattered 3D Vector Fields Radial Basis Functions Approximation Using Space Subdivision

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Computational Science and Its Applications – ICCSA 2019 (ICCSA 2019)

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Abstract

The Radial basis function (RBF) approximation is an efficient method for scattered scalar and vector data fields. However its application is very difficult in the case of large scattered data. This paper presents RBF approximation together with space subdivision technique for large vector fields.

For large scattered data sets a space subdivision technique with overlapping 3D cells is used. Blending of overlapped 3D cells is used to obtain continuity and smoothness. The proposed method is applicable for scalar and vector data sets as well. Experiments proved applicability of this approach and results with the tornado large vector field data set are presented.

The research was supported by projects Czech Science Foundation (GACR) No. GA17-05534S and partially by SGS 2019-016.

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Notes

  1. 1.

    Data set of EF5 tornado courtesy of Leigh Orf from Cooperative Institute for Meteorological Satellite Studies, University of Wisconsin, Madison, WI, USA.

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Acknowledgments

The authors would like to thank their colleagues at the University of West Bohemia, Plzen, for their discussions and suggestions. The research was supported by projects Czech Science Foundation (GACR) No. GA17-05534S and partially by SGS 2019-016.

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Authors and Affiliations

  1. Faculty of Applied Sciences, University of West Bohemia, Plzen, Czech Republic

    Michal Smolik & Vaclav Skala

Authors
  1. Michal Smolik
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  2. Vaclav Skala
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Corresponding author

Correspondence to Michal Smolik .

Editor information

Editors and Affiliations

  1. Covenant University, Ota, Nigeria

    Sanjay Misra

  2. University of Perugia, Perugia, Italy

    Osvaldo Gervasi

  3. University of Basilicata, Potenza, Italy

    Beniamino Murgante

  4. Saint Petersburg State University, Saint Petersburg, Russia

    Elena Stankova

  5. Saint Petersburg State University, Saint Petersburg, Russia

    Vladimir Korkhov

  6. Polytechnic University of Bari, Bari, Italy

    Carmelo Torre

  7. University of Minho, Braga, Portugal

    Ana Maria A.C. Rocha

  8. Monash University, Clayton, VIC, Australia

    David Taniar

  9. Kyushu Sangyo University, Fukuoka, Japan

    Bernady O. Apduhan

  10. Polytechnic University of Bari, Bari, Italy

    Eufemia Tarantino

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Smolik, M., Skala, V. (2019). Efficient Simple Large Scattered 3D Vector Fields Radial Basis Functions Approximation Using Space Subdivision. In: Misra, S., et al. Computational Science and Its Applications – ICCSA 2019. ICCSA 2019. Lecture Notes in Computer Science(), vol 11619. Springer, Cham. https://doi.org/10.1007/978-3-030-24289-3_25

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  • DOI: https://doi.org/10.1007/978-3-030-24289-3_25

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  • Online ISBN: 978-3-030-24289-3

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