Visualization of multidimensional data in explorative forecast

  • Authors:
  • Diana Domańska;Marek Wojtylak;Wiesław Kotarski

  • Affiliations:
  • Institute of Computer Science, University of Silesia, Sosnowiec, Poland;Institute of Meteorology and Water Management (IMGW), Katowice, Poland;Institute of Computer Science, University of Silesia, Sosnowiec, Poland

  • Venue:
  • ICCVG'12 Proceedings of the 2012 international conference on Computer Vision and Graphics
  • Year:
  • 2012

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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.