Visualization of Multidimensional Data in Explorative Forecast

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.

[1]  Yi Lu Murphey,et al.  Multi-class pattern classification using neural networks , 2007, Pattern Recognit..

[2]  J. Scott Armstrong,et al.  Principles of forecasting , 2001 .

[3]  Richard A. Johnson,et al.  Applied Multivariate Statistical Analysis , 1983 .

[4]  Andrew Mercer,et al.  Noodles: A Tool for Visualization of Numerical Weather Model Ensemble Uncertainty , 2010, IEEE Transactions on Visualization and Computer Graphics.

[5]  Elpiniki I. Papageorgiou,et al.  A new methodology for Decisions in Medical Informatics using fuzzy cognitive maps based on fuzzy rule-extraction techniques , 2011, Appl. Soft Comput..

[6]  Diana Domanska,et al.  Application of fuzzy time series models for forecasting pollution concentrations , 2012, Expert Syst. Appl..

[7]  Yi Lu Murphey,et al.  Multiclass pattern classification using neural networks , 2004, ICPR 2004.

[8]  Diana Domanska,et al.  Change a Sequence into a Fuzzy Number , 2010, ADMA.

[9]  Isabelle Bloch,et al.  Fuzzy mathematical morphologies: A comparative study , 1995, Pattern Recognit..

[10]  Tommy W. S. Chow,et al.  PRSOM: a new visualization method by hybridizing multidimensional scaling and self-organizing map , 2005, IEEE Transactions on Neural Networks.

[11]  John W. Sammon,et al.  A Nonlinear Mapping for Data Structure Analysis , 1969, IEEE Transactions on Computers.

[12]  Diana Domańska,et al.  Fuzzy weather forecast in forecasting pollution concentrations , 2010 .

[13]  Jonathan Goldstein,et al.  When Is ''Nearest Neighbor'' Meaningful? , 1999, ICDT.

[14]  Lotfi A. Zadeh,et al.  Fuzzy Sets , 1996, Inf. Control..

[15]  Richard A. Johnson,et al.  Applied multivariate statistical analysis / Richard A. Johnson, Dean W. Wichern , 1992 .