• DocumentCode
    707652
  • Title

    Cognitive neural network modeling of the trajectory of global technical and economic development

  • Author

    Gorbachev, Sergey ; Syryamkin, Vladimir

  • Author_Institution
    Dept. of Innovative Technol., Nat. Res. Tomsk State Univ., Tomsk, Russia
  • fYear
    2015
  • fDate
    3-4 March 2015
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    The article considers the problem of measuring the level and rate of technical and economic development of countries in terms of technological change. Advantages of cognitive neural network approach to monitoring and quality analysis for integrating into a single model of economic, scientific-technological, innovative and other quantitative and qualitative components of growth, not amenable to traditional statistical analysis, with calculation of the forecast evaluation time of the reference trajectory of technical and economic development. Presents the results of the calculations. To improve the accuracy of the model trajectories are encouraged to use self-organizing Kohonen maps.
  • Keywords
    economics; self-organising feature maps; cognitive neural network modeling; economic development; self-organizing Kohonen maps; statistical analysis; technical development; technological change; Analytical models; Economic indicators; Mathematical model; Neural networks; Technological innovation; Trajectory; global modeling; indicators; innovation; neural networks; prediction; the trajectory of technical and economic development;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cognitive Computing and Information Processing (CCIP), 2015 International Conference on
  • Conference_Location
    Noida
  • Type

    conf

  • DOI
    10.1109/CCIP.2015.7100697
  • Filename
    7100697