• DocumentCode
    3396021
  • Title

    Research of the risk assessment of thermal power project investment based on Artificial Neural Networks

  • Author

    Yonggui He ; Chang Liu ; Tianxiang Huang

  • Author_Institution
    Sch. of Bus. Adm., North China Electr. Power Univ., Baoding, China
  • fYear
    2011
  • fDate
    19-22 Aug. 2011
  • Firstpage
    1710
  • Lastpage
    1713
  • Abstract
    This paper according to the investment phase of thermal power projects analyzes the risk factors affecting project investment, on this basis, establishes risk assessment index system of thermal power project investment, and proposes a viable risk assessment model based on BP (Back Propagation) neural network. This model uses BP neural network´s self-learning feature, through amending the weight constantly in the training process, to make the network´s actual output vector be close to the expecting output value gradually. Through simulation of the example by MATLAB neural network tool, the author verifies the reliability of the model, the study of the example shows that this method provides an effective management tool for the risk assessment of thermal power project investment.
  • Keywords
    backpropagation; investment; mathematics computing; neural nets; power engineering computing; project management; risk management; thermal power stations; MATLAB neural network tool; artificial neural network; back propagation neural network; risk assessment index system; self-learning feature; thermal power project investment; training process; Biological neural networks; Investments; Mathematical model; Risk management; Thermal analysis; Thermal management; BP neural network; model; risk assessment; thermal power projects;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Mechatronic Science, Electric Engineering and Computer (MEC), 2011 International Conference on
  • Conference_Location
    Jilin
  • Print_ISBN
    978-1-61284-719-1
  • Type

    conf

  • DOI
    10.1109/MEC.2011.6025810
  • Filename
    6025810