• DocumentCode
    3518912
  • Title

    Economic Adjustment Analysis Based on Artificial Neural Network

  • Author

    Jian, Chen ; Wei, You ; Xin, Tian Jin

  • Author_Institution
    Sch. of Manage., Harbin Inst. of Technol.
  • fYear
    2006
  • fDate
    5-7 Oct. 2006
  • Firstpage
    1189
  • Lastpage
    1192
  • Abstract
    This study is based on neural networks approach trained from the input and output data of economic system as samples. The analytical data used in this study is from Beijing statistical yearbook. After normalizing the data to meet the training requirement and using the method of neural network ensemble, the net which represents the inter-relationship between input and output items of the economic system has been built. By altering input items, observing the effects on output items, we made an analysis for economy adjusting. And the constraints according to the real contradictions between the input items are set in the simulation process. Then by changing the specific two items which constitute a couple of contradiction within a proper range, we observed the developing trends of the output items. The results show trends of output items are reasonable, and several useful conclusions have been draw
  • Keywords
    economic forecasting; mathematics computing; neural nets; Beijing statistical yearbook; MATLAB; artificial neural network; economic adjustment analysis; economic forecasting; economic system; Artificial intelligence; Artificial neural networks; Data analysis; Economic forecasting; Environmental economics; Management training; Mathematical model; Neural networks; Power generation economics; Technology management; Artificial neural networks; Economic adjustment; Economic forecast; MATLB;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Management Science and Engineering, 2006. ICMSE '06. 2006 International Conference on
  • Conference_Location
    Lille
  • Print_ISBN
    7-5603-2355-3
  • Type

    conf

  • DOI
    10.1109/ICMSE.2006.314212
  • Filename
    4105075