Neural Network Analytics and Forecasting the Country's Business Climate in Conditions of the Coronavirus Disease (Covid-19)

- Semerikov, Serhiy O. (orcid.org/0000-0003-0789-0272), Kucherova, Hanna (orcid.org/0000-0002-8635-6758), Los, Vita (orcid.org/0000-0002-7932-5232) and Ocheretin, Dmytro (orcid.org/0000-0001-6705-6381) (2020) Neural Network Analytics and Forecasting the Country's Business Climate in Conditions of the Coronavirus Disease (Covid-19) In: Information Technology and Interactions (Satellite): Conference Proceedings, December 04, 2020, Kyiv, Ukraine . Stylos, c. Kyiv, Ukraine, pp. 42-45. ISBN 978-966-2399-61-5

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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.

Item Type:	Book Section
Keywords:	Business climate, Business confidence index, Correlation analysis, Socio-economic indicators, Taxonomic model, Neural network model, COVID-19
Subjects:	Science and knowledge. Organization. Computer science. Information. Documentation. Librarianship. Institutions. Publications > 00 Prolegomena. Fundamentals of knowledge and culture. Propaedeutics > 004 Computer science and technology. Computing. Data processing > 004.9 ІКТ ( Application-oriented computer-based techniques ) > 004.94 Simulation Science and knowledge. Organization. Computer science. Information. Documentation. Librarianship. Institutions. Publications > 3 Social Sciences > 33 Economics. Economic science
Divisions:	Institute for Digitalisation of Education > Department of the Cloud-Вased Systems of ICT in Education
Depositing User:	Сергій Олексійович Семеріков
Date Deposited:	19 Nov 2021 22:06
Last Modified:	19 Nov 2021 22:06
URI:	https://lib.iitta.gov.ua/id/eprint/726871

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