• DocumentCode
    2763797
  • Title

    A Study of Credit Card Risk Detection Based on Chaos Theory and Neural Network

  • Author

    Zhu, Yan-Li ; Guo, Xiao-Juan ; Wang, Shun-Ping ; Cheng, Ji-Fu

  • Author_Institution
    Sch. of Inf. Eng., Henan Inst. of Sci. & Technol., Xinxiang, China
  • Volume
    1
  • fYear
    2010
  • fDate
    6-7 March 2010
  • Firstpage
    29
  • Lastpage
    31
  • Abstract
    In this paper, a new prediction model, based on chaos theory and BP artificial neural network, is developed to predict the risk of credit card transactions. Embedding dimension of phase-space reconstruction is used to determine network structure, and overcomes the dependence on large amount of samples. Experiments shows that the method based on combination of chaos theory and neural network can improve the accuracy and speed of forecasting.
  • Keywords
    Accuracy; Artificial neural networks; Chaos; Computer networks; Credit cards; Libraries; Mathematical model; Neural networks; Predictive models; Weather forecasting; artificial neural network; chaos theory; phase-space reconstruction; risk detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Challenges in Environmental Science and Computer Engineering (CESCE), 2010 International Conference on
  • Conference_Location
    Wuhan, China
  • Print_ISBN
    978-0-7695-3972-0
  • Electronic_ISBN
    978-1-4244-5924-7
  • Type

    conf

  • DOI
    10.1109/CESCE.2010.211
  • Filename
    5493332
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2763797