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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)

Abstract

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.

Keywords

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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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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