[HTML][HTML] Machine learning and mixed reality for smart aviation: Applications and challenges

Y Jiang, TH Tran, L Williams - Journal of Air Transport Management, 2023 - Elsevier
The aviation industry is a dynamic and ever-evolving sector. As technology advances and
becomes more sophisticated, the aviation industry must keep up with the changing trends …

An application of dbscan clustering for flight anomaly detection during the approach phase

K Sheridan, TG Puranik, E Mangortey… - AIAA Scitech 2020 …, 2020 - arc.aiaa.org
Safety is of paramount importance in aviation due to the catastrophic consequences of
accidents. Consequently, efforts have been made over the years to research and improve …

[HTML][HTML] Augmented reality in the construction industry: use-cases, benefits, obstacles, and future trends

H Nassereddine, AS Hanna, D Veeramani… - Frontiers in Built …, 2022 - frontiersin.org
Information is the lifeblood of modern construction. Advances in Information and
Communication Technology have been and are continuing to progress at rapid rates …

Application of machine learning techniques to parameter selection for flight risk identification

E Mangortey, D Monteiro, J Ackley, Z Gao… - AIAA scitech 2020 …, 2020 - arc.aiaa.org
In recent years, the use of data mining and machine learning techniques for safety analysis,
incident and accident investigation, and fault detection has gained traction among the …

TabNet-SHAP: A Framework to Estimate Wind Shear-Induced Aviation Turbulence in the Airport Runway Vicinity

A Khattak, J Zhang, P Chan, F Chen, AH Almaliki… - IEEE …, 2024 - ieeexplore.ieee.org
In this research, we present an advanced predictive framework designed to assess the
turbulence induced by low-level wind shear near the runways at Hong Kong International …

Airport capacity prediction with multisource features: A temporal deep learning approach

W Du, S Chen, H Li, Z Li, X Cao… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
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 …

Aircraft landing and takeoff operations clustering for efficient environmental impact assessment

A Behere, L Isakson, TG Puranik, Y Li, M Kirby… - AIAA Aviation 2020 …, 2020 - arc.aiaa.org
To maintain sustainable growth of the global air transportation industry, it is crucial to ensure
that the environmental effects of landing and takeoff (LTO) operations are suitably mitigated …

Unscented Kalman filter-aided long short-term memory approach for wind nowcasting

J Kim, K Lee - Aerospace, 2021 - mdpi.com
Obtaining reliable wind information is critical for efficiently managing air traffic and airport
operations. Wind forecasting has been considered one of the most challenging tasks in the …

Terminal Traffic Situation Prediction Model under the Influence of Weather Based on Deep Learning Approaches

L Yuan, Y Zeng, H Chen, J Jin - Aerospace, 2022 - mdpi.com
In order to quantify the degree of influence of weather on traffic situations in real time, this
paper proposes a terminal traffic situation prediction model under the influence of weather …

A hybrid Ensemble Machine Learning approach for arrival flight delay classification prediction using voting aggregation technique

DB Bisandu, I Moulitsas - AIAA AVIATION 2023 Forum, 2023 - arc.aiaa.org
View Video Presentation: https://doi. org/10.2514/6.2023-4326. vid The number of flights
keeps increasing with the development of civil aviation, and flight delays have become a …