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ИД «Финансы и кредит»






Finance and Credit

Evolutionary neural network modeling of import substitution in the electronics industry of regions

Vol. 30, Iss. 4, APRIL 2024

Received: 13 November 2023

Received in revised form: 27 November 2023

Accepted: 11 December 2023

Available online: 26 April 2024

Subject Heading: INVESTING

JEL Classification: C32, C45, L63, O21, O32

Pages: 765–787


Sergei N. YASHIN National Research Lobachevsky State University of Nizhny Novgorod (UNN), Nizhny Novgorod, Russian Federation


Egor V. KOSHELEV National Research Lobachevsky State University of Nizhny Novgorod (UNN), Nizhny Novgorod, Russian Federation


Dmitrii A. SUKHANOV Non-State Educational Private Institution for Advanced Vocational Education Biota – Plus, Nizhny Novgorod, Russian Federation


Subject. This article focuses on the issues of evolutionary neural network modeling of import substitution capabilities and opportunities.
Objectives. The article aims to study evolutionary neural network modeling in terms of identifying opportunities for import substitution in the electronics industry in the regions of Russia. The article also aims to identify the regions that are leaders in terms of the possibility of import substitution, and the regions that have prospects for the future development of the electronics industry within their territory.
Results. The article presents the author-developed methodology for evolutionary neural network modeling of the possibility of import substitution in the electronics industry of the regions.
Conclusions and Relevance. The results obtained can be useful for government agencies to plan the import substitution process in the electronics industry in regions mentioned. Investors can also use these results to choose the area of capital investment of their funds.

Keywords: adaptive neuro fuzzy inference system, particle swarm optimization, time series prediction, radio electronics industry


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ISSN 2311-8709 (Online)
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Vol. 30, Iss. 4
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