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
Link To Document