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

Author:

YASHIN Sergei N.1ORCID,KOSHELEV Egor V.1ORCID,SUKHANOV Dmitrii A.2ORCID

Affiliation:

1. National Research Lobachevsky State University of Nizhny Novgorod (UNN)

2. Non-State Educational Private Institution for Advanced Vocational Education Biota – Plus

Abstract

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.

Funder

Russian Science Foundation

Publisher

Publishing House Finance and Credit

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