Forecasting Model of Non-Scheduled Passenger Air Transportation in Fuzzy Approach

In this paper, we delve into the conceptual underpinnings of fuzzy logic and its applicability to forecasting within the context of non-scheduled passenger air transportation. We review relevant literature, highlighting the limitations of traditional forecasting techniques and the rationale for adopting a fuzzy approach. Additionally, we outline the methodology employed in developing the proposed fuzzy forecasting model, emphasizing its adaptability to evolving operational conditions and its potential to enhance decision-making processes within the aviation industry. In the conducted research, a new method of building a forecasting model using a fuzzy approach was proposed for the time series of non-scheduled passenger air transportation with intra- series multiplicative changes. The method is based on the use of membership functions in the calculation of forecast values based on statistical indicators of intra-row changes. In regular air transportation, the intra-series changes of statistical indicators of time series 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 in charter air transportation. Therefore, to solve the problem, we propose to build the forecasting model of non-scheduled passenger air transportation using a fuzzy approach. The researched method was checked based on the actual data of the time series of charter flights. The obtained results were compared with classical forecasting models (ARIMA, Fine, Medium, and Coarse SVM), and it was noted that the results were obtained within acceptable limits.