期刊论文

Liu, John J.

英文

Journal of Air Transport Management

0969-6997

2014

39

1-11

10.1016/j.jairtraman.2014.03.004

本校为第一机构

Air transport demand forecasting is receiving increasing attention, especially because of intrinsic difficulties and practical applications. Total passengers are used as a proxy for air transport demand. However, the air passenger time series usually has a complex behavior due to their irregularity, high volatility and seasonality. This paper proposes a new hybrid approach, combining singular spectrum analysis (SSA), adaptive-network-based fuzzy inference system (ANFIS) and improved particle swarm optimization (IPSO), for yshort-term air passenger traffic prediction. The SSA is used for identi...