Visualization of Multidimensional Data in Explorative Forecast

  • Diana Domańska
  • Marek Wojtylak
  • Wiesław Kotarski
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7594)


The aim of this paper is to present a new way of multidimensional data visualization for explorative forecast built for real meteorological data coming from the Institute of Meteorology and Water Management (IMGW) in Katowice, Poland. In the earlier works two first authors of the paper proposed a method that aggregates huge amount of data based on fuzzy numbers. Explorative forecast uses similarity of data describing situations in the past to those in the future. 2D and 3D visualizations of multidimensional data can be used to carry out its analysis to find hidden information that is not visible in the raw data e.g. intervals of fuzziness, fitting real number to a fuzzy number.


Fuzzy Number Weather Forecast Pollution Concentration Data Cube Multidimensional Data 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Armstrong, J.S.: Principles of Forecasting, pp. 1–12. Kluwer Academic Publishers, Norwell (2002) ISBN 0-306-47630-4Google Scholar
  2. 2.
    Beyer, K.S., Goldstein, J., Ramakrishnan, R., Shaft, U.: When is ”Nearest Neighbour” meaningful? In: Proc. of the 7th Int. Conf. on Database Theory, pp. 217–235 (1999)Google Scholar
  3. 3.
    Bloch, I., Maitre, H.: Fuzzy Mathematical Morphologies: a Comparative Study. Pattern Recognition 28(9), 1341–1387 (1995)MathSciNetCrossRefGoogle Scholar
  4. 4.
    Domańska, D., Wojtylak, M.: Application of Fuzzy Time Series Models for Forecasting Pollution Concentrations. Expert Systems with Applications 39(9), 7673–7679 (2012)CrossRefGoogle Scholar
  5. 5.
    Domańska, D., Wojtylak, M.: Change a Sequence into a Fuzzy Number. In: Cao, L., Zhong, J., Feng, Y. (eds.) ADMA 2010, Part II. LNCS, vol. 6441, pp. 55–62. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  6. 6.
    Domańska, D., Wojtylak, M.: Fuzzy Weather Forecast in Forecasting Pollution Concentrations. In: Proc. of Chaotic Modeling and Simulation International Conference, CD Version (2010)Google Scholar
  7. 7.
    Johnson, R.A., Wichern, D.W.: Applied Multivariate Statistical Analysis. Prentice-Hall, Englewood Cliffs (1992)zbMATHGoogle Scholar
  8. 8.
    Koronacki, J., Ćwik, J.: Statistical Learning Systems. Ed. 2, Exit, Warszawa (2008) (in Polish)Google Scholar
  9. 9.
    Ou, G., Murphey, Y.L.: Multi-class Pattern Classification using Neural Networks. Pattern Recognition 40(1), 4–18 (2007)CrossRefzbMATHGoogle Scholar
  10. 10.
    Papageorgiou, E.I.: A New Methodology for Decisions in Medical Informatics using Fuzzy Cognitive Maps Based on Fuzzy Rule-extraction Techniques. Applied Soft Computing 11(1), 500–513 (2011)CrossRefGoogle Scholar
  11. 11.
    Sammon, J.W.: A Nonlinear Mapping for Data Structure Analysis. IEEE Transactions on Computers 18(5), 401–409 (1969)CrossRefGoogle Scholar
  12. 12.
    Sanyal, J., Dyer, S.Z., Mercer, J., Amburn, A., Moorhead, P., Noodles, R.J.: Noodles: A Tool for Visualization of Numerical Weather Model Ensemble Uncertainty. IEEE Transactions on Visualization and Computer Graphics 16(6), 1421–1430 (2010)CrossRefGoogle Scholar
  13. 13.
    Shepard, R.N., Carroll, J.D.: Parametric Representation of Nonlinear Data Structures. In: Krishnaiah, P.R. (ed.) Proceedings of the International Symposium on Multivariate Analysis, pp. 561–592. Academic, New York (1965)Google Scholar
  14. 14.
    Wu, S., Chow, T.W.S.: PRSOM: a New Visualization Method by Hybridizing Multidimensional Scaling and Self-organizing Map. IEEE Transactions on Neural Networks 16(6), 1362–1380 (2005)CrossRefGoogle Scholar
  15. 15.
    Zadeh, L.: Fuzzy Sets. Information and Control 8(3), 338–353 (1965)MathSciNetCrossRefzbMATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Diana Domańska
    • 1
  • Marek Wojtylak
    • 2
  • Wiesław Kotarski
    • 1
  1. 1.Institute of Computer ScienceUniversity of SilesiaSosnowiecPoland
  2. 2.Institute of Meteorology and Water Management (IMGW)KatowicePoland

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