Assessment of Region Economic Development on the Basis of Neural Network Model
Abstract The paper considers the possibility to use neural network modeling for assessing the economic development of regions exemplified by the Arctic region of the Russian Federation – Murmansk region. The paper presents assessing and reasoning of this usage, describes its opportunities and threat...
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crioppubl:10.1088/1755-1315/302/1/012094 2024-06-02T08:02:11+00:00 Assessment of Region Economic Development on the Basis of Neural Network Model Antipov, S K Bocharov, A A Kobicheva, A Krasnozhenova, E E 2019 http://dx.doi.org/10.1088/1755-1315/302/1/012094 https://iopscience.iop.org/article/10.1088/1755-1315/302/1/012094/pdf https://iopscience.iop.org/article/10.1088/1755-1315/302/1/012094 unknown IOP Publishing http://creativecommons.org/licenses/by/3.0/ https://iopscience.iop.org/info/page/text-and-data-mining IOP Conference Series: Earth and Environmental Science volume 302, issue 1, page 012094 ISSN 1755-1307 1755-1315 journal-article 2019 crioppubl https://doi.org/10.1088/1755-1315/302/1/012094 2024-05-07T14:05:16Z Abstract The paper considers the possibility to use neural network modeling for assessing the economic development of regions exemplified by the Arctic region of the Russian Federation – Murmansk region. The paper presents assessing and reasoning of this usage, describes its opportunities and threats. The author analyzes four indicators as main economic characteristics: gross regional product, an amount of investments into the fixed capital, retail turnover, foreign trade turnover. The study shows which factors have the most significant effect on these characteristics and comments on the obtained results. The author describes methodology of building the model and checks it empirically. In order to assess the model more accurately, it includes autoregression elements, which allows estimating not only direct interaction, but monitoring possible temporary inertia. Assessment results based on neural network modeling are compared with the results obtained on the basis of ADL equations (autoregressive distributed lag model). Accuracy of the final calculations is analyzed with using the mean absolute percentage error (MAPE) in further preference to the model of neural networks. Article in Journal/Newspaper Arctic IOP Publishing Arctic Murmansk IOP Conference Series: Earth and Environmental Science 302 1 012094 |
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description |
Abstract The paper considers the possibility to use neural network modeling for assessing the economic development of regions exemplified by the Arctic region of the Russian Federation – Murmansk region. The paper presents assessing and reasoning of this usage, describes its opportunities and threats. The author analyzes four indicators as main economic characteristics: gross regional product, an amount of investments into the fixed capital, retail turnover, foreign trade turnover. The study shows which factors have the most significant effect on these characteristics and comments on the obtained results. The author describes methodology of building the model and checks it empirically. In order to assess the model more accurately, it includes autoregression elements, which allows estimating not only direct interaction, but monitoring possible temporary inertia. Assessment results based on neural network modeling are compared with the results obtained on the basis of ADL equations (autoregressive distributed lag model). Accuracy of the final calculations is analyzed with using the mean absolute percentage error (MAPE) in further preference to the model of neural networks. |
format |
Article in Journal/Newspaper |
author |
Antipov, S K Bocharov, A A Kobicheva, A Krasnozhenova, E E |
spellingShingle |
Antipov, S K Bocharov, A A Kobicheva, A Krasnozhenova, E E Assessment of Region Economic Development on the Basis of Neural Network Model |
author_facet |
Antipov, S K Bocharov, A A Kobicheva, A Krasnozhenova, E E |
author_sort |
Antipov, S K |
title |
Assessment of Region Economic Development on the Basis of Neural Network Model |
title_short |
Assessment of Region Economic Development on the Basis of Neural Network Model |
title_full |
Assessment of Region Economic Development on the Basis of Neural Network Model |
title_fullStr |
Assessment of Region Economic Development on the Basis of Neural Network Model |
title_full_unstemmed |
Assessment of Region Economic Development on the Basis of Neural Network Model |
title_sort |
assessment of region economic development on the basis of neural network model |
publisher |
IOP Publishing |
publishDate |
2019 |
url |
http://dx.doi.org/10.1088/1755-1315/302/1/012094 https://iopscience.iop.org/article/10.1088/1755-1315/302/1/012094/pdf https://iopscience.iop.org/article/10.1088/1755-1315/302/1/012094 |
geographic |
Arctic Murmansk |
geographic_facet |
Arctic Murmansk |
genre |
Arctic |
genre_facet |
Arctic |
op_source |
IOP Conference Series: Earth and Environmental Science volume 302, issue 1, page 012094 ISSN 1755-1307 1755-1315 |
op_rights |
http://creativecommons.org/licenses/by/3.0/ https://iopscience.iop.org/info/page/text-and-data-mining |
op_doi |
https://doi.org/10.1088/1755-1315/302/1/012094 |
container_title |
IOP Conference Series: Earth and Environmental Science |
container_volume |
302 |
container_issue |
1 |
container_start_page |
012094 |
_version_ |
1800746676641595392 |