Artificial intelligence technologies as a factor in increasing the economic efficiency of generating companies

The article deals with the application of modern artificial intelligence technologies that affect the economic efficiency of generating companies. Scientific novelty lies in the approach to the consideration of artificial intelligence as both external and internal factors of influence on the dynamic...

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Main Authors: Troianova Elena, Lerman Evgenia, Baliasnikova Elena, Fiutik Ina, Savelieva Ekaterina
Format: Article
Language:English
Published: EDP Sciences 2021-01-01
Series:E3S Web of Conferences
Online Access:https://www.e3s-conferences.org/articles/e3sconf/pdf/2021/64/e3sconf_suse2021_01067.pdf
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spelling doaj-ca72e1dae29f44f09484d841b8792cb12021-07-15T06:53:02ZengEDP SciencesE3S Web of Conferences2267-12422021-01-012880106710.1051/e3sconf/202128801067e3sconf_suse2021_01067Artificial intelligence technologies as a factor in increasing the economic efficiency of generating companiesTroianova ElenaLerman Evgenia0Baliasnikova Elena1Fiutik Ina2Savelieva Ekaterina3Siberian Transport University, Novosibirsk, Russian FederationWestern Branch of the Russian Academy of National Economy and Public Administration under the President of the Russian FederationSiberian State University of Water TransportSiberian State University of Water TransportThe article deals with the application of modern artificial intelligence technologies that affect the economic efficiency of generating companies. Scientific novelty lies in the approach to the consideration of artificial intelligence as both external and internal factors of influence on the dynamics of production and consumption of electricity. As a result of the study, the key aspects of the growth of the economic efficiency of the activities of energy generating companies are highlighted and characterized. The forecast of the prospective sustainable development of certain areas of the energy sector and the increase in energy consumption is presented.https://www.e3s-conferences.org/articles/e3sconf/pdf/2021/64/e3sconf_suse2021_01067.pdf
collection DOAJ
language English
format Article
sources DOAJ
author Troianova Elena
Lerman Evgenia
Baliasnikova Elena
Fiutik Ina
Savelieva Ekaterina
spellingShingle Troianova Elena
Lerman Evgenia
Baliasnikova Elena
Fiutik Ina
Savelieva Ekaterina
Artificial intelligence technologies as a factor in increasing the economic efficiency of generating companies
E3S Web of Conferences
author_facet Troianova Elena
Lerman Evgenia
Baliasnikova Elena
Fiutik Ina
Savelieva Ekaterina
author_sort Troianova Elena
title Artificial intelligence technologies as a factor in increasing the economic efficiency of generating companies
title_short Artificial intelligence technologies as a factor in increasing the economic efficiency of generating companies
title_full Artificial intelligence technologies as a factor in increasing the economic efficiency of generating companies
title_fullStr Artificial intelligence technologies as a factor in increasing the economic efficiency of generating companies
title_full_unstemmed Artificial intelligence technologies as a factor in increasing the economic efficiency of generating companies
title_sort artificial intelligence technologies as a factor in increasing the economic efficiency of generating companies
publisher EDP Sciences
series E3S Web of Conferences
issn 2267-1242
publishDate 2021-01-01
description The article deals with the application of modern artificial intelligence technologies that affect the economic efficiency of generating companies. Scientific novelty lies in the approach to the consideration of artificial intelligence as both external and internal factors of influence on the dynamics of production and consumption of electricity. As a result of the study, the key aspects of the growth of the economic efficiency of the activities of energy generating companies are highlighted and characterized. The forecast of the prospective sustainable development of certain areas of the energy sector and the increase in energy consumption is presented.
url https://www.e3s-conferences.org/articles/e3sconf/pdf/2021/64/e3sconf_suse2021_01067.pdf
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