Short-term forecasting of the main indicators of the COVID-19 epidemic in Ukraine based on the seasonal cycle model
The authors of this study propose a method of short-term forecasting of time series of the main indicators of the COVID-19 epidemic, which has a pronounced seasonality. This method, which has no direct analogies, provides the decomposition of a general forecasting task into several simpler tasks, su...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | Ukrainian |
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Igor Sikorsky Kyiv Polytechnic Institute
2024-12-01
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| Series: | Sistemnì Doslìdženâ ta Informacìjnì Tehnologìï |
| Subjects: | |
| Online Access: | http://journal.iasa.kpi.ua/article/view/322459 |
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| _version_ | 1850037023360942080 |
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| author | Alexei Alyokhin Anna Brutman Alexandr Grabovoy Tetiana Shabelnyk |
| author_facet | Alexei Alyokhin Anna Brutman Alexandr Grabovoy Tetiana Shabelnyk |
| author_sort | Alexei Alyokhin |
| collection | DOAJ |
| description | The authors of this study propose a method of short-term forecasting of time series of the main indicators of the COVID-19 epidemic, which has a pronounced seasonality. This method, which has no direct analogies, provides the decomposition of a general forecasting task into several simpler tasks, such as the tasks of building a model of the seasonal cycle of a time series, aggregating the original time series, taking into account the duration of the seasonal cycle, forecasting an aggregated time series, developing an aggregated forecast into a forecast in the original time scale, using the seasonal cycle model. The solution for each task allows the usage of relatively simple methods of mathematical statistics. The article provides a formally rigorous description of all procedures of the method and illustrations of their numerical implementation on the example of a real forecasting task. The use of this method for short-term forecasting of the COVID-19 epidemic development in Ukraine has systematically demonstrated its effectiveness. |
| format | Article |
| id | doaj-art-33db635373f4441db82e81c85cad18bc |
| institution | DOAJ |
| issn | 1681-6048 2308-8893 |
| language | Ukrainian |
| publishDate | 2024-12-01 |
| publisher | Igor Sikorsky Kyiv Polytechnic Institute |
| record_format | Article |
| series | Sistemnì Doslìdženâ ta Informacìjnì Tehnologìï |
| spelling | doaj-art-33db635373f4441db82e81c85cad18bc2025-08-20T02:56:59ZukrIgor Sikorsky Kyiv Polytechnic InstituteSistemnì Doslìdženâ ta Informacìjnì Tehnologìï1681-60482308-88932024-12-014324210.20535/SRIT.2308-8893.2024.4.02361174Short-term forecasting of the main indicators of the COVID-19 epidemic in Ukraine based on the seasonal cycle modelAlexei Alyokhin0https://orcid.org/0000-0001-5209-8036Anna Brutman1https://orcid.org/0000-0002-7774-5356Alexandr Grabovoy2https://orcid.org/0000-0001-5705-9909Tetiana Shabelnyk3https://orcid.org/0000-0001-9798-391XMariupol State University, KyivNational University “Zaporizhzhia Polytechnic”, ZaporizhzhiaBogomolets National Medical University, KyivSimon Kuznets Kharkiv National University of Economics, KharkivThe authors of this study propose a method of short-term forecasting of time series of the main indicators of the COVID-19 epidemic, which has a pronounced seasonality. This method, which has no direct analogies, provides the decomposition of a general forecasting task into several simpler tasks, such as the tasks of building a model of the seasonal cycle of a time series, aggregating the original time series, taking into account the duration of the seasonal cycle, forecasting an aggregated time series, developing an aggregated forecast into a forecast in the original time scale, using the seasonal cycle model. The solution for each task allows the usage of relatively simple methods of mathematical statistics. The article provides a formally rigorous description of all procedures of the method and illustrations of their numerical implementation on the example of a real forecasting task. The use of this method for short-term forecasting of the COVID-19 epidemic development in Ukraine has systematically demonstrated its effectiveness.http://journal.iasa.kpi.ua/article/view/322459covid-19 epidemictime seriesshort-term forecastingseasonal cycleindicators |
| spellingShingle | Alexei Alyokhin Anna Brutman Alexandr Grabovoy Tetiana Shabelnyk Short-term forecasting of the main indicators of the COVID-19 epidemic in Ukraine based on the seasonal cycle model Sistemnì Doslìdženâ ta Informacìjnì Tehnologìï covid-19 epidemic time series short-term forecasting seasonal cycle indicators |
| title | Short-term forecasting of the main indicators of the COVID-19 epidemic in Ukraine based on the seasonal cycle model |
| title_full | Short-term forecasting of the main indicators of the COVID-19 epidemic in Ukraine based on the seasonal cycle model |
| title_fullStr | Short-term forecasting of the main indicators of the COVID-19 epidemic in Ukraine based on the seasonal cycle model |
| title_full_unstemmed | Short-term forecasting of the main indicators of the COVID-19 epidemic in Ukraine based on the seasonal cycle model |
| title_short | Short-term forecasting of the main indicators of the COVID-19 epidemic in Ukraine based on the seasonal cycle model |
| title_sort | short term forecasting of the main indicators of the covid 19 epidemic in ukraine based on the seasonal cycle model |
| topic | covid-19 epidemic time series short-term forecasting seasonal cycle indicators |
| url | http://journal.iasa.kpi.ua/article/view/322459 |
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