• DocumentCode
    2228372
  • Title

    A Hybrid GA-BP Model for Bankruptcy Prediction

  • Author

    Sai, Ying ; Zhong, Chenjian ; Qu, Lehong

  • Author_Institution
    Sch. of Comput. & Inf. Eng., Shandong Univ. of Finance, Jinan
  • fYear
    2007
  • fDate
    21-23 March 2007
  • Firstpage
    473
  • Lastpage
    477
  • Abstract
    With the increase of economic globalization and evolution of information technology, accounting information are being generated and accumulated at an unprecedented pace. As a result, there has been a critical need for automated approaches to effective and efficient utilization of massive amount of accounting information to support companies´ decision making. In this paper, we describe a hybrid GA-BP model in bankruptcy prediction. Optimization based on the genetic algorithm was executed on the neural networks thresholds and weights values. In addition, an example is given to validate the model; the results show our model has a high prediction accuracy in bankruptcy prediction
  • Keywords
    accounts data processing; backpropagation; decision making; genetic algorithms; neural nets; accounting information; backpropagation; bankruptcy prediction; decision making; economic globalization; genetic algorithm; information technology; neural networks; Accuracy; Artificial neural networks; Economic forecasting; Finance; Genetic algorithms; Neural networks; Neurons; Performance analysis; Power generation economics; Predictive models;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Autonomous Decentralized Systems, 2007. ISADS '07. Eighth International Symposium on
  • Conference_Location
    Sedona, AZ
  • Print_ISBN
    0-7695-2804-X
  • Type

    conf

  • DOI
    10.1109/ISADS.2007.3
  • Filename
    4144704