• DocumentCode
    2972261
  • Title

    The Evaluation of Success Degree in Electric Power Engineering Project Based on Principal Component Analysis and Fuzzy Neural Network

  • Author

    Duan, Baoqian ; Tang, Yun ; Tian, Li ; Liu, Qingchao

  • Author_Institution
    Dept. of Econ. & Manage., North China Electr. Power Univ., Baoding
  • fYear
    2008
  • fDate
    2-3 Aug. 2008
  • Firstpage
    339
  • Lastpage
    344
  • Abstract
    Using principal component analysis (PCA) and improved fuzzy neural network by PSO to evaluate the success degree in electric power engineering is this paper´s innovative points. First we construct the algorithm model which based on PCA and BP neural network improved by PSO. Secondly using PCA to predigest the given index system and then using the relative membership degree processing the date, which as the input sample of neural network. Thirdly, use the improved BP neural network by PSO to evaluate the success degree of electric power engineering. The result denotes that it is more accuracy and speedily than BP neural network algorithm. Lastly, we give a real engineering, and get a satisfaction result.
  • Keywords
    backpropagation; fuzzy neural nets; particle swarm optimisation; power engineering computing; principal component analysis; BP neural network; PSO; electric power engineering project; fuzzy neural network; particle swarm optimisation; principal component analysis; Clustering algorithms; Fuzzy neural networks; Intelligent networks; Intelligent transportation systems; Investments; Neural networks; Power electronics; Power engineering and energy; Principal component analysis; Project management; PSO; evaluating degree of success; neural network; principal component analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power Electronics and Intelligent Transportation System, 2008. PEITS '08. Workshop on
  • Conference_Location
    Guangzhou
  • Print_ISBN
    978-0-7695-3342-1
  • Type

    conf

  • DOI
    10.1109/PEITS.2008.9
  • Filename
    4634872