| ITI əməkdaşlarının elmi işləri - tezis |
| Biblioqrafik təsvir | |
| Hajirahimova , M.S. Using machine learning to estimate the effect of vaccination process on COVID-19 cases and deaths in Azerbaijan / M.S. Hajirahimova , A.S. Aliyeva // Национальный Суперкомпьютерный Форум (НСКФ-2021) . - Moskva, 2021. - P. 1-5. | |
| Annotasiya | |
| Currently, the COVID-19 pandemic has become a worldwide health problem. In order to control the number of cases, many countries have taken various measures such as quarantine, curfew and closing social areas for a while. The researchers in many countries are in search of a solution to end up this pandemic. An unprecedented research effort and global coordination has resulted in a rapid development of vaccine candidates and initiation of trials. There is a strong consensus globally that a COVID-19 vaccination is one of the most effective and cost effective methods of combating infectious diseases in modern times. Vaccines have helped reduce the incidence and mortality of many diseases, have saved mankind from infectious diseases over the past century. This paper, an effort has been made to find the correlation between vaccination and confirmed cases and death cases. For this purpose, k-means clustering-based machine learning method has been employed on the data set of Azerbaijan, which has been obtained from the GitHub repository of the Center for Systems Science and Engineering at Johns Hopkins University from April 1, 2021 until September 27, 2021. | |
| Elektron variant | |
| Elektron variant |
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