A Reproducible and Regime-Aware SARIMA Modelling Framework for National Air Traffic Forecasting: Evidence from Türkiye (2018-2025)
MODELLING, cilt.7, sa.2, 2026 (ESCI)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 7 Sayı: 2
- Basım Tarihi: 2026
- Doi Numarası: 10.3390/modelling7020077
- Dergi Adı: MODELLING
- Derginin Tarandığı İndeksler: Emerging Sources Citation Index (ESCI)
- Anahtar Kelimeler: adaptive conformal inference, air traffic forecasting, bootstrap, conformal prediction, cross-validation, Diebold–Mariano test, prediction intervals, rolling-origin, SARIMA, structural break
- Erciyes Üniversitesi Adresli: Evet
Özet
Reliable short-term air traffic forecasts are important for operational planning in national airspace systems. This study develops a transparent forecasting framework for T & uuml;rkiye's monthly aircraft movements using publicly available data from the General Directorate of State Airports Authority (DHM & Idot;) for 2018-2025. Because DHM & Idot; releases may follow cumulative within-year reporting, month-specific increments are reconstructed through within-year differencing and checked through simple audit procedures. The empirical analysis compares seasonal na & iuml;ve, ETS, and a constrained SARIMA family under leakage-free evaluation, combining a strict 2025 holdout with expanding-window rolling-origin validation. Forecast performance is assessed using standard accuracy metrics and complemented by Diebold-Mariano comparisons, which are interpreted cautiously, given the short holdout length. To examine instability around the pandemic period, this study also reports structural-break and stability diagnostics as supportive evidence rather than definitive identification. Uncertainty is evaluated through backtested 80% and 95% prediction intervals, comparing nominal SARIMA intervals, parametric bootstrap, split conformal prediction, and adaptive conformal inference (ACI). The results show that SARIMA provides the strongest point-forecast performance among the benchmarked models, while adaptive conformal calibration offers a useful balance between empirical coverage and interval width under changing conditions. Overall, this study provides a reproducible and operationally interpretable baseline for national air traffic forecasting in T & uuml;rkiye and a clear benchmark for future multivariate extensions.