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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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
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spelling doaj-d8a90c6155994f7594b519f55767ab5c2021-04-02T12:16:38ZengEDP SciencesE3S Web of Conferences2267-12422020-01-011641004510.1051/e3sconf/202016410045e3sconf_tpacee2020_10045The use of neural networks and a genetic algorithm for modeling the innovative environment of enterprisesSviridova Svetlana0Shkarupeta Elena1Dorokhova Olga2Voronezh Technical State UniversityVoronezh Technical State UniversityMoscow Suvorov Military SchoolThe 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.https://www.e3s-conferences.org/articles/e3sconf/pdf/2020/24/e3sconf_tpacee2020_10045.pdf
collection DOAJ
language English
format Article
sources DOAJ
author Sviridova Svetlana
Shkarupeta Elena
Dorokhova Olga
spellingShingle Sviridova Svetlana
Shkarupeta Elena
Dorokhova Olga
The use of neural networks and a genetic algorithm for modeling the innovative environment of enterprises
E3S Web of Conferences
author_facet Sviridova Svetlana
Shkarupeta Elena
Dorokhova Olga
author_sort Sviridova Svetlana
title The use of neural networks and a genetic algorithm for modeling the innovative environment of enterprises
title_short The use of neural networks and a genetic algorithm for modeling the innovative environment of enterprises
title_full The use of neural networks and a genetic algorithm for modeling the innovative environment of enterprises
title_fullStr The use of neural networks and a genetic algorithm for modeling the innovative environment of enterprises
title_full_unstemmed The use of neural networks and a genetic algorithm for modeling the innovative environment of enterprises
title_sort use of neural networks and a genetic algorithm for modeling the innovative environment of enterprises
publisher EDP Sciences
series E3S Web of Conferences
issn 2267-1242
publishDate 2020-01-01
description 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.
url https://www.e3s-conferences.org/articles/e3sconf/pdf/2020/24/e3sconf_tpacee2020_10045.pdf
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