Creating a Forecasting Model of Passenger Flows in Non-Scheduled Air Transportation

In the article, a new method of building a forecast model using a fuzzy approach for charter air transportation time series with intra-series multiplicative changes is proposed. The method is based on the use of correlation functions in the calculation of forecast values based on statistical indicators of intra-row changes. In regular air transportation, the changes in the time series of statistical indicators are stable. On charter flights, these changes are unstable. This is due to the strong random effects of external factors (a sudden increase in demand for flights, economic changes, etc.) on the formation of charter flights. For this reason, the application of models based on trend changes does not give good enough results when building forecast models for charter flights. Therefore, to solve the problem, we propose to build a forecast model using a fuzzy approach, using the randomness of the intra-series changes of the statistical indicators of this type of air transportation. The researched method was checked based on the actual data of the time series of charter flights, and the results were obtained within acceptable limits.