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Research of the innovative development of the Russian Federation regions and its impact on the eco-friendliness of the economy based on neural network cluster analysis for the purpose of economic security

机译:俄罗斯联邦地区创新发展及其对经济性经济宗旨基于神经网络聚类分析的基于神经网络聚类分析的影响研究

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This article is devoted to the assessment of innovative development of the Russian Federation regions using self-organizing Kohonen maps. The relevance of this paper is due to the need to develop various criteria for making decisions on state support for regions, the use of which will allow to conduct a comprehensive assessment of regional development. Its findings should serve as a reliable, high-quality source of information about the feasibility and type of support for a particular region. The study provides a justification for a set of indicators that are used in conducting cluster analysis. The methodology developed by the authors provides an opportunity to divide the regions into clusters, conduct their quantitative and qualitative analysis, and further predict the key indicators of the regions based on their belonging to different clusters. All this allows to study regional innovative development in dynamics. The authors draw a conclusion about the uneven innovative development of the Russian regions and the ambiguity of connections between the indicators of the share of organizations engaged in technological innovations and the degree of environmental friendliness of the economy. The findings of this study will be useful to public authorities when making decisions on the allocation of budgetary funds for the development of territories.
机译:本文致力于使用自组织科隆地图评估俄罗斯联邦地区的创新发展。本文的相关性是由于需要开发各种标准,以制定国家支持地区的决策,使用这将允许对区域发展进行全面评估。其调查结果应作为可靠,高质量的信息来源,了解特定区域的可行性和类型的类型。该研究提供了一组指标的理由,用于进行集群分析。作者开发的方法提供了将区域分成集群的机会,进行其定量和定性分析,并进一步预测地区的关键指标,基于其属于不同的群集。这一切允许研究动态的区域创新发展。作者提出了俄罗斯地区的不均匀创新发展的结论以及从事技术创新的组织份额和经济环境友好程度的组织份额之间的联系的歧义。该研究的调查结果将对公共当局有助于作出决定,为各国领土的发展分配。

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