A knee-guided evolutionary algorithm for multi-objective air traffic flow management
Air traffic flow management plays a crucial role in efficient aviation. Most existing studies
assume the flight speed as constant throughout the trip, leading to ineffective fixed-speed …
assume the flight speed as constant throughout the trip, leading to ineffective fixed-speed …
A multi-objective memetic algorithm with adaptive local search for airspace complexity mitigation
Airspace complexity is a paramount safety metric to measure the difficulty and effort required
to safely manage air traffic. The continuing growth in air traffic demand results in increasing …
to safely manage air traffic. The continuing growth in air traffic demand results in increasing …
Determination of air traffic complexity most influential parameters based on machine learning models
F Pérez Moreno, VF Gómez Comendador… - Symmetry, 2022 - mdpi.com
Today, aircraft demand is exceeding the capacity of the Air Traffic Control (ATC) system. As
a result, airspace is becoming a very complex environment to control. The complexity of …
a result, airspace is becoming a very complex environment to control. The complexity of …
How Has the Concept of Air Traffic Complexity Evolved? Review and Analysis of the State of the Art of Air Traffic Complexity
F Pérez Moreno, VF Gómez Comendador… - Applied Sciences, 2024 - mdpi.com
Featured Application Application of main conclusions when developing a complexity
indicator for giving information about air traffic. Abstract Air traffic complexity is an indicator …
indicator for giving information about air traffic. Abstract Air traffic complexity is an indicator …
[HTML][HTML] Methodology of air traffic flow clustering and 3-D prediction of air traffic density in ATC sectors based on machine learning models
FP Moreno, VFG Comendador, RDA Jurado… - Expert Systems with …, 2023 - Elsevier
The increase in the demand for aircraft operations has caused the ATM system to become
overloaded as it no longer has sufficient capacity to respond to this increase in demand. For …
overloaded as it no longer has sufficient capacity to respond to this increase in demand. For …
A spatiotemporal hybrid model for airspace complexity prediction
Airspace complexity is a key indicator that reflects the safety of airspace operations in air
traffic management systems. Furthermore, to achieve efficient air traffic control, it is …
traffic management systems. Furthermore, to achieve efficient air traffic control, it is …
A Spatial-Temporal Approach for Multi-Airport Traffic Flow Prediction Through Causality Graphs
Accurate airport traffic flow estimation is crucial for the secure and orderly operation of the
aviation system. Recent advances in machine learning have achieved promising prediction …
aviation system. Recent advances in machine learning have achieved promising prediction …
MAST-GNN: A multimodal adaptive spatio-temporal graph neural network for airspace complexity prediction
Airspace complexity is defined as an essential indicator to comprehensively measure the
safety of air traffic operational situations. A reliable prediction of airspace complexity can …
safety of air traffic operational situations. A reliable prediction of airspace complexity can …
Airport capacity prediction with multisource features: A temporal deep learning approach
Accurate airport capacity estimation is crucial for the secure and orderly operation of the
aviation system. However, such estimation is a non-trivial task as capacity depends on …
aviation system. However, such estimation is a non-trivial task as capacity depends on …
Short-term multi-step-ahead sector-based traffic flow prediction based on the attention-enhanced graph convolutional LSTM network (AGC-LSTM)
Accurate sector-based air traffic flow predictions are essential for ensuring the safety and
efficiency of the air traffic management (ATM) system. However, due to the inherent spatial …
efficiency of the air traffic management (ATM) system. However, due to the inherent spatial …