Airport arrival and departure movements are characterized by high dynamism, stochasticity,
and uncertainty. Therefore, it is of paramount importance to predict and analyze surface taxi …

Airport taxi delays adversely affect airports and airlines around the world leading to airside
congestion, increased Air Traffic Controllers/Pilot workload, and adverse environmental …

The increasing availability of A-CDM (Airport-Collaborative Decision system) data gives the
opportunity to better understand the airport ground operation. Taxi time, as one of the key …

Airside taxi delays have adverse consequences for airports and airlines globally, leading to
airside congestion, increased Air Traffic Controller/Pilot workloads, missed passenger …

The prediction of taxi time plays a primary role. To improve the accuracy and portability of
prediction, the Informer-RFR (Informer-Random Forest Regression) model was proposed …

Increasing availability of air traffic data has opened new opportunities for better
understanding of Air Traffic Management (ATM) system. At Airport-Air side, A-SMGCS (Ad …

Variable taxi time prediction is the core of the Airport Collaborative Decision Making (A-
CDM) system. An accurate taxi time prediction contributes to enhancing airport operational …

Taxi time, as one of the key indicators to evaluate the airport operation efficiency, will not
only have a direct impact on the takeoff and landing sequence of the runway, but also affect …

There is an increasing interest in developing Intelligent Decision Support Systems (IDSSs)
for various aviation operations such as resource planning. Recently, with the significant …

Asia has witnessed a meteoric rise in its air traffic in the last decade; leading the region to
experience the fastest air traffic growth, globally. However, air traffic infrastructure has not …