• DocumentCode
    3057078
  • Title

    Application of Unascertained Neural Networks to Financial Early Warning

  • Author

    Shi Huawang

  • Author_Institution
    Sch. of Civil Eng., Hebei Univ. of Eng., Handan, China
  • Volume
    2
  • fYear
    2009
  • fDate
    22-24 May 2009
  • Firstpage
    365
  • Lastpage
    368
  • Abstract
    Artificial neural network (ANN) has outstanding characteristics in machine learning, fault, tolerant, parallel reasoning and processing nonlinear problem abilities. Unascertained system that imitates the human brain´s thinking logical is a kind of mathematical tools used to deal with imprecise and uncertain knowledge. Integrating unascertained method with neural network technology, the reasoning process of network coding can be tracked, and the output of the network can be given a physical explanation. A unascertained neural network was set up. It can be compared with the fuzzy network, so that their own advantages and shortcomings can be found and further study can be made on the uncertainty network to improve the uncertainty network more complete.
  • Keywords
    financial data processing; learning (artificial intelligence); neural nets; artificial neural network; financial early warning; fuzzy network; machine learning; network coding; neural network technology; parallel reasoning; processing nonlinear problem; unascertained method; unascertained neural network; unascertained system; uncertain knowledge; uncertainty network; Artificial neural networks; Biological neural networks; Civil engineering; Electronic commerce; Electronic mail; Humans; Machine learning; Network coding; Neural networks; Uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electronic Commerce and Security, 2009. ISECS '09. Second International Symposium on
  • Conference_Location
    Nanchang
  • Print_ISBN
    978-0-7695-3643-9
  • Type

    conf

  • DOI
    10.1109/ISECS.2009.133
  • Filename
    5209797