Author

F. Piurcosky

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Open access Jul 2026

LOGISTICS AND TRANSPORTATION: FREIGHT DEMAND FORECASTING USING SARIMA AND XGBOOST

This study compares the performance of two forecasting approaches—Seasonal Autoregressive Integrated Moving Average (SARIMA) and Extreme Gradient Boosting) for predicting daily freight demand measured by transported weight and demonstrates that feature engineering substantially improved predictive performance.

Eduardo Modesto de Melo, F. Piurcosky · Revista Mythos · 0 citations