A Neural Network Measurement of the Level and Pace of Global Economic and Technological Development

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.