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

机译:认知神经网络建模全球技术与经济发展轨迹

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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.
机译:本文考虑了在技术变革方面衡量各国技术和经济发展水平和经济发展率的问题。认知神经网络的优点是监测和质量分析,融合到一个经济,科技,创新和其他定性和定性成分的单一模型,不适合传统统计分析,计算预测评估时间技术和经济发展的参考轨迹。呈现计算结果。为了提高模型轨迹的准确性,鼓励使用自组织科隆地图。

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