Virology: Current Research

Dr, Department of Data Analysis and Machine Learning, Financial University under the Government of the Russian Federation, Moscow, Russia

Publications

• Research Article   
  Methodology for Predicting the Number of Cases of COVID-19 Using Neural Technologies on the Example of Russian Federation and Moscow
  Author(s): Edward Dadyan*
  
  The analyst often must deal with data that represents the history of changes in various objects over time, with time series. They are the ones that are most interesting from the point of view of many analysis tasks, and especially forecasting. For analysis tasks, time counts are of interest-values recorded at some, usually equidistant, points in time. Counts can be taken at various intervals: in a minute, an hour, a day, a week, a month, or a year, depending on how much detail the process should be analyzed. In time series analysis problems, we are dealing with discrete time, when each observation of a parameter forms a time frame. We can say the same about the behavior of COVID-19 over time. This paper solves the problem of predicting COVID-19 diseases in Moscow and the Russian Federation using neural networks. This approach is useful when it is necessary to overco.. Read More»
  DOI: 10.37421/2736-657X.2023.07.002

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