The use of neural networks and a genetic algorithm for modeling the innovative environment of enterprises

The purpose of this paper is to develop methodological tools for building the innovative environment of enterprises using the genetic algorithm and neural networks. The paper analyzes and highlights the advantages of genetic algorithms in the search for optimal solutions compared to classical method...

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Bibliographic Details
Main Authors: Sviridova Svetlana, Shkarupeta Elena, Dorokhova Olga
Format: Article
Language:English
Published: EDP Sciences 2020-01-01
Series:E3S Web of Conferences
Online Access:https://www.e3s-conferences.org/articles/e3sconf/pdf/2020/24/e3sconf_tpacee2020_10045.pdf
Description
Summary:The purpose of this paper is to develop methodological tools for building the innovative environment of enterprises using the genetic algorithm and neural networks. The paper analyzes and highlights the advantages of genetic algorithms in the search for optimal solutions compared to classical methods. The scheme of construction of each step of the genetic algorithm is described in detail; the scheme of the presentation of artificial neural network data in key factors of innovative development of enterprises is given. The aspects of using neural networks of attractors and a genetic algorithm for modeling the processes of the innovative environment of enterprises are considered. The key problem of introducing effective industrial innovations is the lack of a favorable climatic environment that stimulates the creation of innovations that ensure the growth of global competitiveness, labor productivity and the quality of life of the population. The result of the study is the formation of a model of the innovative environment of enterprises based on the use of neural networks and a genetic algorithm.
ISSN:2267-1242