Air traffic forecasting using statistical analysis and machine learning methods
Abstract:
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.
