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

• المؤلفون الرئيسيون: GUO, Xiaojia, GRUSHKA-COCKAYNE, Yael, REYCK, Bert De
• التنسيق: text
• اللغة: English
• منشور في: Institutional Knowledge at Singapore Management University 2022
• الموضوعات: quantile forecasts; regression tree; copula; passenger flow management; data-driven operations; Numerical Analysis and Scientific Computing; Operations and Supply Chain Management; Transportation
• الوصول للمادة أونلاين: https://ink.library.smu.edu.sg/lkcsb_research/7628

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...