Beyond route-specific forecasting: An empirical test of two cross-series transfer learning strategies for airline demand with short-data constraints | Synapse
March 3, 2026
Beyond route-specific forecasting: An empirical test of two cross-series transfer learning strategies for airline demand with short-data constraints
Puntos clave
Effective cross-series transfer learning strategies improve airline demand forecasting under short-data constraints.
The study demonstrates how limited data can still yield accurate predictions in airline demand.
Using empirical testing, two strategies are evaluated for their forecasting capabilities across different routes.
Findings highlight the potential for enhanced forecasting methods, indicating the need to adapt to data limitations.