• DocumentCode
    2074751
  • Title

    On post-evaluation of power plant construction project based on improved back propagation neural network

  • Author

    Niu Dongxiao ; Li Xin ; Zhang Kun ; Liu Yimin

  • Author_Institution
    Sch. of Econ. & Manage., North China Electr. Power Univ., Beijing, China
  • fYear
    2010
  • fDate
    29-31 July 2010
  • Firstpage
    2458
  • Lastpage
    2461
  • Abstract
    Construction project post-evaluation is the feedback link of the project decision management, and it can provide a scientific basis for construction projects in the future. This paper established the post-evaluation indicator system of power plant construction project according to its feature. Based on the improved back propagation neural network by using adaptive learning rate and momentum algorithm, combined with Delphi method and success degree method, the post-evaluation model was established. Through the empirical study on 300 MW power plant construction projects, compared with the traditional back propagation neural network model, the result of improved BP neural network model is more accurate and effective.
  • Keywords
    backpropagation; construction; decision making; neural nets; power plants; project management; 300MW power plant construction projects; Delphi method; adaptive learning rate; back propagation neural network; momentum algorithm; post evaluation; project decision management; success degree method; Adaptation model; Artificial neural networks; Construction industry; Equations; Mathematical model; Power generation; Training; Improved BP Neural Network; Post-evaluation; Power Plant Construction Project;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Conference (CCC), 2010 29th Chinese
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4244-6263-6
  • Type

    conf

  • Filename
    5572187