Assessing the Level of Production Potential of the Regions of Ukraine with Use of Neural Networks

The problem of improvement of methods of estimation of level of development of regions of Ukraine on production potential on the basis of building of integrated indicators and carrying out of clustering has been considered. It has been proposed to apply an integrated approach to analysis of the aggr...

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Main Authors: Kravets Tetyana V., Verhai Tetiana I.
Format: Article
Language:English
Published: Research Centre of Industrial Problems of Development of NAS of Ukraine 2017-11-01
Series:Bìznes Inform
Subjects:
Online Access:http://www.business-inform.net/export_pdf/business-inform-2017-11_0-pages-112_119.pdf
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spelling doaj-89d3a412c3c5404383fdaf6cec7736612020-11-24T23:40:47ZengResearch Centre of Industrial Problems of Development of NAS of UkraineBìznes Inform2222-44592311-116X2017-11-0111478112119Assessing the Level of Production Potential of the Regions of Ukraine with Use of Neural NetworksKravets Tetyana V.0Verhai Tetiana I.1Candidate of Sciences (Physics and Mathematics), Associate Professor, Associate Professor, Department of Economic Cybernetics, Kyiv National University named after T. ShevchenkoStudent, Kyiv National University named after T. Shevchenko The problem of improvement of methods of estimation of level of development of regions of Ukraine on production potential on the basis of building of integrated indicators and carrying out of clustering has been considered. It has been proposed to apply an integrated approach to analysis of the aggregate of indicators of the regions’ performance, characterizing the production potential, with the purpose of constructing integrated indicators by different approaches and with subsequent clustering of regions using the Kohonen neural networks. Use of the Kohonen maps along with database clustering allowed to design multidimensional data in a two-dimensional space, to carry out an analysis of the resulting cluster system, and to improve the results of clustering by selecting the optimal quantity of split groups. The convenient form of visualization of results of clustering provides for localizing features and making the corresponding corrections in the rating list, proceeding from expert judgments.http://www.business-inform.net/export_pdf/business-inform-2017-11_0-pages-112_119.pdfproduction potentialKohonen neural networklevel of development of regionsintegral estimation
collection DOAJ
language English
format Article
sources DOAJ
author Kravets Tetyana V.
Verhai Tetiana I.
spellingShingle Kravets Tetyana V.
Verhai Tetiana I.
Assessing the Level of Production Potential of the Regions of Ukraine with Use of Neural Networks
Bìznes Inform
production potential
Kohonen neural network
level of development of regions
integral estimation
author_facet Kravets Tetyana V.
Verhai Tetiana I.
author_sort Kravets Tetyana V.
title Assessing the Level of Production Potential of the Regions of Ukraine with Use of Neural Networks
title_short Assessing the Level of Production Potential of the Regions of Ukraine with Use of Neural Networks
title_full Assessing the Level of Production Potential of the Regions of Ukraine with Use of Neural Networks
title_fullStr Assessing the Level of Production Potential of the Regions of Ukraine with Use of Neural Networks
title_full_unstemmed Assessing the Level of Production Potential of the Regions of Ukraine with Use of Neural Networks
title_sort assessing the level of production potential of the regions of ukraine with use of neural networks
publisher Research Centre of Industrial Problems of Development of NAS of Ukraine
series Bìznes Inform
issn 2222-4459
2311-116X
publishDate 2017-11-01
description The problem of improvement of methods of estimation of level of development of regions of Ukraine on production potential on the basis of building of integrated indicators and carrying out of clustering has been considered. It has been proposed to apply an integrated approach to analysis of the aggregate of indicators of the regions’ performance, characterizing the production potential, with the purpose of constructing integrated indicators by different approaches and with subsequent clustering of regions using the Kohonen neural networks. Use of the Kohonen maps along with database clustering allowed to design multidimensional data in a two-dimensional space, to carry out an analysis of the resulting cluster system, and to improve the results of clustering by selecting the optimal quantity of split groups. The convenient form of visualization of results of clustering provides for localizing features and making the corresponding corrections in the rating list, proceeding from expert judgments.
topic production potential
Kohonen neural network
level of development of regions
integral estimation
url http://www.business-inform.net/export_pdf/business-inform-2017-11_0-pages-112_119.pdf
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