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http://elibrary.kdpu.edu.ua/xmlui/handle/123456789/4133Повний запис метаданих
| Поле DC | Значення | Мова |
|---|---|---|
| dc.contributor.author | Семеріков, Сергій Олексійович | - |
| dc.contributor.author | Kucherova, Hanna | - |
| dc.contributor.author | Los, Vita | - |
| dc.contributor.author | Ocheretin, Dmytro | - |
| dc.date.accessioned | 2020-12-24T19:50:35Z | - |
| dc.date.available | 2020-12-24T19:50:35Z | - |
| dc.date.issued | 2020-12-23 | - |
| dc.identifier.citation | Semerikov S. Neural Network Analytics and Forecasting the Country's Business Climate in Conditions of the Coronavirus Disease (Covid-19) / Serhiy Semerikov, Hanna Kucherova, Vita Los, Dmytro Ocheretin // Information Technology and Interactions (Satellite): Conference Proceedings, December 04, 2020, Kyiv, Ukraine / Taras Shevchenko National University of Kyiv and [etc] ; Vitaliy Snytyuk (Editor). – Kyiv, 2020. – Pp. 42-45. | uk_UA |
| dc.identifier.isbn | 978-966-2399-61-5 | - |
| dc.identifier.uri | http://elibrary.kdpu.edu.ua/xmlui/handle/123456789/4133 | - |
| dc.identifier.uri | https://doi.org/10.31812/123456789/4133 | - |
| dc.description | 1. S. Arslankaya, V. Oz. Sakarya, Time Series Analysis on Sales Quantity in an Automotive Company and Estimation by Artificial Neural Networks. University Journal of Science 22, 1482-1492 (2018). doi: 10.16984/saufenbilder.456518. 2. D. Ocheretin, V. Los, H. Kucherova, O. Bilska, An alternative approach to modeling the country's business climate in conditions of limited information. E3SWC 166 (2020): 13024. URL: https://www.e3s-conferences.org/articles/e3sconf/abs/2020/26/e3sconf_icsf2020_13024/e3sconf_ icsf2020_13024.html. 3. L.A. El'shin, Mechanisms for the identification of business cycles of regional economic systems based on cross-correlation analysis. Regional Economics: Theory and Practice 15(8), 1540- 1551 (2017). doi: 10.24891/re.15.8.1540. 4. V. Los, D. Ocheretin, H. Kucherova, O. Bilska, Neural network technology forecasting the country's business climate, in: Hryhoruk, P., Khrushch, N. (eds.), Proceedings of the 6th International Conference on Strategies, Models and Technologies of Economic Systems Management (SMTESM 2019) 95, pp. 320-324. Atlantis Press (2019). DOI: 10.2991/smtesm-19.2019.62. 5. M. R. Safiullin, L.A. El'shin, A.I. Shakirova, Evaluation of business and economic activity as a short-term forecasting tool. Herald of the Russian Academy of Sciences 82(4), 623-627 (2012). doi: 10.1134/S1019331612040053 6. S. Feuerriegela, J. Gordon, News-based forecasts of macroeconomic indikators : a semantic path model for interpretable predictions. European Journal of Operational Research 272(1), 162-175 (2019). doi: 10.1016/j.ejor.2018.05.068. 7. H. F. Mendonca, A. F. G. Almeida, Importance of credibility for business confidence: evidence from an emerging economy. Empirical Economics (2018). doi: 10.1007/s00181-018-1533-5. 8. H. Sakaji, R. Kuramoto, H. Matsushima, K. Izumi, T. Shimada, K. Sunakawa, Financial Text Data Analytics Framework for Business Confidence Indices and Inter-Industry Relations, in: Proceedings of the First Workshop on Financial Technology and Natural Language Processing (FinNLP@IJCAI 2019), pp. 40-46. Macao, China (2019). 9. V. Los, D. Ocheretin, Construction of business confidence index based on a system of economic indicators, in: Semerikov, S., Soloviev, V., Kibalnyk, L., Chernyak, O., Danylchuk, H. (eds.) SHS Web of Conference. The 8th International Conference on Monitoring, Modeling & Management of Emergent Economy (M3E2 2019), vol.65, pp. 1-6. SHS Web of Conferences (2019). doi: 10.1051/shsconf/20196506003. | - |
| dc.description.abstract | The paper proposes an approach to modeling the business climate of the country, which is based on the principles of information transparency, and makes it possible to assess the development trends of the studied indicator in conditions of the COVID-19. This approach has been tested on the example of Ukraine. The results obtained make it possible to analyze the cyclical development of the country's economy with high accuracy and reliability even under quarantine restrictions. | uk_UA |
| dc.language.iso | en | uk_UA |
| dc.publisher | Stylos | uk_UA |
| dc.subject | business climate | uk_UA |
| dc.subject | business confidence index | uk_UA |
| dc.subject | correlation analysis | uk_UA |
| dc.subject | socio-economic indicators | uk_UA |
| dc.subject | taxonomic model | uk_UA |
| dc.subject | neural network model | uk_UA |
| dc.subject | COVID-19 | uk_UA |
| dc.title | Neural Network Analytics and Forecasting the Country's Business Climate in Conditions of the Coronavirus Disease (Covid-19) | uk_UA |
| dc.type | Article | uk_UA |
| Розташовується у зібраннях: | Кафедра інформатики та прикладної математики | |
Файли цього матеріалу:
| Файл | Опис | Розмір | Формат | |
|---|---|---|---|---|
| SemerikovKucherovaLosOcheretin.pdf | abstract | 1.2 MB | Adobe PDF | Переглянути/Відкрити |
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