Neural network modelling for determining the priority areas of regional development

Описание

Тип публикации: доклад, тезисы доклада, статья из сборника материалов конференций

Конференция: IOP Publishing Ltd; 27 August 2020 through 29 August 2020; 27 August 2020 through 29 August 2020

Год издания: 2020

Идентификатор DOI: 10.1088/1757-899X/986/1/012017

Аннотация: Neural network modeling based on self-organizing Kohonen maps was carried out in order to cluster the economy of one of the administrative districts of the Krasnoyarsk Territory. The research is based on statistical data on the economy of about one hundred enterprises of various spheres operating in the region. It is shown that in Показать полностьюthe process of clustering four groups of enterprises can be clearly distinguished according to the types of economic activity. Having applied the neural network modelling method, we identified three enterprises within the framework of this cluster, which can be considered as "growth areas"of the district economy. Self-organizing maps that is trained using unsupervised learning make it possible to get an idea not only of promising areas of development, but also to identify key parameters that ensure the leadership and competitiveness of the region. © 2020 Published under licence by IOP Publishing Ltd.

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Издание

Журнал: IOP Conference Series: Materials Science and Engineering

Выпуск журнала: Vol. 986, Is. 1

ISSN журнала: 00165825

Персоны

  • Moskalev A.K. (Siberian Federal University, Kirensky St. 28, Krasnoyarsk, 660074, Russian Federation)
  • Petrunina A.E. (Siberian Federal University, Kirensky St. 28, Krasnoyarsk, 660074, Russian Federation)
  • Tsygankov N.S. (Siberian Federal University, Kirensky St. 28, Krasnoyarsk, 660074, Russian Federation)

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