Comparative analysis of forecasting methods for demand and prices in the freight transportation market
Abstract
Comparative analysis of forecasting methods for demand and prices in the freight transportation market
Incoming article date: 11.10.2025The article presents a comparative analysis of the forecasting accuracy of five methods for demand and price time series: classical statistical approaches, machine learning algorithms, and a deep learning architecture.
Keywords: time series forecasting, road freight transportation, machine learning, gradient boosting, recurrent neural networks, comparative analysis of forecasting methods