A survey on artificial intelligence (ai) and explainable ai in air traffic management: Current trends and development with future research trajectory
Air Traffic Management (ATM) will be more complex in the coming decades due to the
growth and increased complexity of aviation and has to be improved in order to maintain …
growth and increased complexity of aviation and has to be improved in order to maintain …
A highway traffic image enhancement algorithm based on improved GAN in complex weather conditions
X Cheng, J Zhou, J Song, X Zhao - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
To address the problems of low resolution and blurred details in highway images caused by
factors such as rain and fog, illumination interference, and nighttime lighting, this paper …
factors such as rain and fog, illumination interference, and nighttime lighting, this paper …
A novel parallel series data-driven model for IATA-coded flight delays prediction and features analysis
Predicting and analysing flight delays is essential for successful air traffic management and
control. We propose a novel parallel-series model and novel adaptive bidirectional extreme …
control. We propose a novel parallel-series model and novel adaptive bidirectional extreme …
Supporting weather forecasting performance management at aerodromes through anomaly detection and hierarchical clustering
Weather forecasting is a critical factor for aerodrome and enroute flight operations. Airport
decision-makers rely on assessments made by forecasters to ensure operations safety and …
decision-makers rely on assessments made by forecasters to ensure operations safety and …
Towards Green Airports: Factors Influencing Greenhouse Gas Emissions and Sustainability through Renewable Energy
M Parhamfar - Next Research, 2024 - Elsevier
Airports are significant energy consumers within the air transport sector, with energy usage
levels comparable to those of small cities. Due to their rapid economic growth and high …
levels comparable to those of small cities. Due to their rapid economic growth and high …
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 …
Weather impact quantification on airport arrival on-time performance through a Bayesian statistics modeling approach
Compared with departures, predicting the weather impact on arrival delays is more
challenging because of possible non-linear, cascading effects, and higher uncertainty …
challenging because of possible non-linear, cascading effects, and higher uncertainty …
[HTML][HTML] A machine learned go-around prediction model using pilot-in-the-loop simulations
Go-around manoeuvers are challenging for the management of arriving air traffic due to their
complexity and unpredictability. In the present work, we propose to augment the air traffic …
complexity and unpredictability. In the present work, we propose to augment the air traffic …
Implementation of a long-range air traffic flow management for the asia-pacific region
We provide a concept of operations and a corresponding implementation of a long-range air
traffic flow management in the Asia-Pacific region. This management will provide an …
traffic flow management in the Asia-Pacific region. This management will provide an …
Predicting flight arrival times with deep learning: A strategy for minimizing potential conflicts in gate assignment
Air transportation is frequently disrupted by factors such as weather and air traffic control,
making it difficult for flights to strictly adhere to schedules, leading to frequent early arrivals …
making it difficult for flights to strictly adhere to schedules, leading to frequent early arrivals …