DocumentCode :
707661
Title :
Cognitive neural network modeling of the trajectory of global technical and economic development
Author :
Gorbachev, Sergey ; Syryamkin, Vladimir
Author_Institution :
Department of Innovative Technologies, National Research Tomsk State University, 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 :
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, India
Type :
conf
DOI :
10.1109/CCIP.2015.7100713
Filename :
7100713
Link To Document :
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