Akademik Veri Yönetim Sistemi
Gazi University Journal of Science Part C: Design and Technology, cilt.11, sa.2, ss.475-485, 2023 (Hakemli Dergi)
The global impact of the COVID-19 pandemic has done great damage to air transportation.
Demand for airline transportation has declined for reasons such as quarantine practices by
countries, curfews, the economic recession, and the transfer of meetings to digital platforms. This
situation has also led to a change in individuals' preferences for air transport. The most noticeable
change in air transport is the tendency of individuals to use air transport privately to minimize the
health risks that face-to-face contact can pose. Individuals who avoid commercial air transport
where public transportation is available have shifted to private airline transportation. For these
reasons, a forecast study was conducted in this study so that a private airline could provide
accurate flight schedules in the future. For the forecast study, the number of aircraft types for
2022 was determined by obtaining data on the number of aircraft by passenger capacity, the
number of flights, and the number of passengers for 2019-2021 from the airline company. Support
Vector Machines (SVM), Gaussian Process Regression (GPR), Regression Trees, and Ensemble
Learning models from machine learning methods were used for the forecasting study. The
performance evaluation of the models used was compared. The model results with the highest
performance evaluation were used. According to the results obtained, it has been found that there
will be an increase of approximately 7% in the number of flights for 2022 compared to the prepandemic period. The findings provided important information for the company's future fleet
planning.