The subject of the presented research is to determine the complete neural procedure for classifying inaccurate information, as given in the form of an interval vector. For such a formulated task, a basic functionality Probabilistic Neural Network was extended upon the interval type of information. As a consequence, a new type of neural network has been proposed. The presented methodology was positively verified using random and benchmark data sets. In addition, a comparative analysis of existing algorithms with similar conditions was made.


neural networks probabilistic neural networks data analysis classification interval data imprecise information 


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© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Piotr A. Kowalski
    • 1
    • 2
  • Piotr Kulczycki
    • 1
    • 2
  1. 1.Department of Automatic Control and Information TechnologyCracow University of TechnologyCracowPoland
  2. 2.Systems Research InstitutePolish Academy of SciencesWarsawPoland

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