Neural network model as a way of processing complex systems of econometric equations characterizing the interaction of the Russian Arctic
This article analyses the possibility of applying neural network modeling for the purpose of automation of a large number of calculations of econometric equations coefficients in order to obtain adequate predictive results.
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EDP Sciences
2018
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Online Access: | https://doi.org/10.1051/matecconf/201817001025 https://doaj.org/article/eeba6e8710a647e28b90777a3d6ec737 |
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ftdoajarticles:oai:doaj.org/article:eeba6e8710a647e28b90777a3d6ec737 2023-05-15T14:53:15+02:00 Neural network model as a way of processing complex systems of econometric equations characterizing the interaction of the Russian Arctic Antipov Sergey 2018-01-01T00:00:00Z https://doi.org/10.1051/matecconf/201817001025 https://doaj.org/article/eeba6e8710a647e28b90777a3d6ec737 EN FR eng fre EDP Sciences https://doi.org/10.1051/matecconf/201817001025 https://doaj.org/toc/2261-236X 2261-236X doi:10.1051/matecconf/201817001025 https://doaj.org/article/eeba6e8710a647e28b90777a3d6ec737 MATEC Web of Conferences, Vol 170, p 01025 (2018) Engineering (General). Civil engineering (General) TA1-2040 article 2018 ftdoajarticles https://doi.org/10.1051/matecconf/201817001025 2022-12-31T15:25:31Z This article analyses the possibility of applying neural network modeling for the purpose of automation of a large number of calculations of econometric equations coefficients in order to obtain adequate predictive results. Article in Journal/Newspaper Arctic Directory of Open Access Journals: DOAJ Articles Arctic MATEC Web of Conferences 170 01025 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English French |
topic |
Engineering (General). Civil engineering (General) TA1-2040 |
spellingShingle |
Engineering (General). Civil engineering (General) TA1-2040 Antipov Sergey Neural network model as a way of processing complex systems of econometric equations characterizing the interaction of the Russian Arctic |
topic_facet |
Engineering (General). Civil engineering (General) TA1-2040 |
description |
This article analyses the possibility of applying neural network modeling for the purpose of automation of a large number of calculations of econometric equations coefficients in order to obtain adequate predictive results. |
format |
Article in Journal/Newspaper |
author |
Antipov Sergey |
author_facet |
Antipov Sergey |
author_sort |
Antipov Sergey |
title |
Neural network model as a way of processing complex systems of econometric equations characterizing the interaction of the Russian Arctic |
title_short |
Neural network model as a way of processing complex systems of econometric equations characterizing the interaction of the Russian Arctic |
title_full |
Neural network model as a way of processing complex systems of econometric equations characterizing the interaction of the Russian Arctic |
title_fullStr |
Neural network model as a way of processing complex systems of econometric equations characterizing the interaction of the Russian Arctic |
title_full_unstemmed |
Neural network model as a way of processing complex systems of econometric equations characterizing the interaction of the Russian Arctic |
title_sort |
neural network model as a way of processing complex systems of econometric equations characterizing the interaction of the russian arctic |
publisher |
EDP Sciences |
publishDate |
2018 |
url |
https://doi.org/10.1051/matecconf/201817001025 https://doaj.org/article/eeba6e8710a647e28b90777a3d6ec737 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic |
genre_facet |
Arctic |
op_source |
MATEC Web of Conferences, Vol 170, p 01025 (2018) |
op_relation |
https://doi.org/10.1051/matecconf/201817001025 https://doaj.org/toc/2261-236X 2261-236X doi:10.1051/matecconf/201817001025 https://doaj.org/article/eeba6e8710a647e28b90777a3d6ec737 |
op_doi |
https://doi.org/10.1051/matecconf/201817001025 |
container_title |
MATEC Web of Conferences |
container_volume |
170 |
container_start_page |
01025 |
_version_ |
1766324702108712960 |