ABSTRACT
This chapter focuses on the model selection and construction of the short-term air travel demand framework, for the complex and volatile economic circumstances, where the common forecasting models may fail with a relatively high probability. It proposes an integrated short-term forecasting framework based on the TEI@I methodology, with the empirical mode decomposition method as a decomposition method. Empirical results show that the proposed method outperforms other competitive forecasting models, indicating that the proposed framework is a promising tool to forecast the short-term air travel demand, under volatile and complex economic circumstances. For years, the air transportation industry has played an important role in the development of the local economy, so it is necessary to provide more accurate demand forecasts for the future development and planning of Hong Kong International Airport (HKIA). In the empirical analysis, the historical passenger movements of HKIA are used as the proxies for air travel demand.
