Forecasting airport transfer passenger flow using real-time data and machine learning

• Main Authors: GUO, Xiaojia, GRUSHKA-COCKAYNE, Yael, REYCK, Bert De
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2022
• Subjects: quantile forecasts; regression tree; copula; passenger flow management; data-driven operations; Numerical Analysis and Scientific Computing; Operations and Supply Chain Management; Transportation
• Online Access: https://ink.library.smu.edu.sg/lkcsb_research/7628
• Institution: Singapore Management University

Problem definition: Airports and airlines have been challenged to improve decision making by producing accurate forecasts in real time. We develop a two-phased predictive system that produces forecasts of transfer passenger flows at an airport. In the first phase, the system predicts the distributio...