• DocumentCode
    3457641
  • Title

    The Application of Power Plant Construction Investment Estimation Based on Improved Neural Network by PSO

  • Author

    Zheng-yuan Jia ; Li Tian ; Qingchao Liu

  • Author_Institution
    Sch. of Bus. Adm., North China Electr. Power Univ., Baoding
  • fYear
    2008
  • fDate
    12-14 Oct. 2008
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Using BP neural network estimate the investment of the power plant construction project is this paper´s innovative points. First we give the engineering characteristic factors of power plant construction project, then give the value of each qualitative index. Then use improved BP neural network by PSO to estimate the investment. From the result, we can see that is more accuracy and speedily than BP neural network algorithm. Lastly, we can get a satisfaction result. This can be guiding the project construction investment.
  • Keywords
    backpropagation; civil engineering computing; construction; investment; neural nets; power plants; BP neural network; improved neural network; power plant construction investment estimation; power plant construction project; Cost function; Extrapolation; Feedforward neural networks; Fuzzy neural networks; Investments; Neural networks; Neurons; Power engineering and energy; Power generation; Project management;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Wireless Communications, Networking and Mobile Computing, 2008. WiCOM '08. 4th International Conference on
  • Conference_Location
    Dalian
  • Print_ISBN
    978-1-4244-2107-7
  • Electronic_ISBN
    978-1-4244-2108-4
  • Type

    conf

  • DOI
    10.1109/WiCom.2008.1756
  • Filename
    4679945