• DocumentCode
    3509066
  • Title

    The Model and Application of the Investment Risk Comprehensive Evaluation about the Electric Power Project Based on BP Neural Network

  • Author

    Liu, Zhibin ; Xiong, Fengshan

  • Author_Institution
    Econ. & Manage. Dept., North China Electr. Power Univ., Baoding
  • fYear
    2007
  • fDate
    21-25 Sept. 2007
  • Firstpage
    5188
  • Lastpage
    5191
  • Abstract
    The power projects face the uncertain external environment, they are complex of the projects themselves and the capabilities of the designers, erectors and operator are limited, which make the risk indicators of the power projects investment are extremely complicated, including financial risk, technology risk, production risk, market risk, management risk and environmental risk In order to evaluate the risk investment projects scientifically and accurately, according to the principle of BP neural network, this paper proposes the BP neural network model for the risk evaluation of the power project investment. The model not only can simulate the expert in evaluating the investing risk, but also avoid the subjective mistakes in the evaluation process. The investment risk evaluation of 16 power projects in National Power Company shows that the results given by this model are reliable, and this method to forecast the power project investment risk is feasible.
  • Keywords
    backpropagation; neural nets; power engineering computing; power system economics; risk management; backpropagation neural network; electric power project; investment risk comprehensive evaluation; Energy management; Environmental management; Financial management; Investments; Neural networks; Predictive models; Production; Project management; Risk management; Technology management;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Wireless Communications, Networking and Mobile Computing, 2007. WiCom 2007. International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4244-1311-9
  • Type

    conf

  • DOI
    10.1109/WICOM.2007.1270
  • Filename
    4341045