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KIAM Preprint № 70, Moscow, 2022
Authors: Sudakov V.A., Timofeev M.A.
Air traffic forecasting using statistical analysis and machine learning methods
The paper considers current methods for forecasting time series on the example of domestic and international transportation of the Russian Federation in recent years, taking into account the influence of external factors. Models were developed using autoregressive moving average and using gradient boosting. The possibility of using data on COVID-19 diseases for forecasting was investigated.
time-series analysis, aviation, ARIMA, SARIMA, gradient boosting
Publication language: russian,  pages: 14
Research direction:
Mathematical modelling in actual problems of science and technics
Russian source text:
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About authors:
  • Sudakov Vladimir Anatolievich, RAS
  • Timofeev Maksim Aleksandrovich, State Budgetary Educational Institution of Higher Education Plekhanov Russian University of Economics