• DocumentCode
    2490094
  • Title

    A hybrid grey-fuzzy-neural networks model for enterprises´ bankruptcy

  • Author

    Scarlat, Emil ; Delcea, Camelia

  • Author_Institution
    Dept. of Cybern., Univ. of Econ., Bucharest, Romania
  • fYear
    2010
  • fDate
    18-23 July 2010
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    This paper attempts to put forward a hybrid model which combines the advantages offered by grey systems theory, fuzzy theory and neural networks. While φ -fuzzy sub-set offers the suitable tools for the treatment of uncertainty and subjectivity, grey systems theory is used for variables selection. Also, neural networks pattern recognition facility is used in order to determine each company´s bankruptcy stage through its interconnection with the other companies that are conducting their business in the same field. Compared with a simple model of pattern recognition, our model succeeded in getting a higher accuracy rate. A numerical example is presented in order to better understand the proposed model.
  • Keywords
    corporate modelling; fuzzy neural nets; fuzzy set theory; grey systems; pattern recognition; φ -fuzzy subset; enterprise bankruptcy; fuzzy set theory; grey systems theory; hybrid grey-fuzzy-neural network model; neural network pattern recognition facility; variable selection; Artificial neural networks; Geology; Technological innovation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks (IJCNN), The 2010 International Joint Conference on
  • Conference_Location
    Barcelona
  • ISSN
    1098-7576
  • Print_ISBN
    978-1-4244-6916-1
  • Type

    conf

  • DOI
    10.1109/IJCNN.2010.5596526
  • Filename
    5596526