Recent advances in anomaly detection methods applied to aviation
Anomaly detection is an active area of research with numerous methods and applications.
This survey reviews the state-of-the-art of data-driven anomaly detection techniques and …
This survey reviews the state-of-the-art of data-driven anomaly detection techniques and …
Aircraft trajectory clustering in terminal airspace based on deep autoencoder and gaussian mixture model
The aircraft trajectory clustering analysis in the terminal airspace is conducive to determining
the representative route structure of the arrival and departure trajectory and extracting their …
the representative route structure of the arrival and departure trajectory and extracting their …
Traffic, a toolbox for processing and analysing air traffic data
X Olive - Journal of Open Source Software, 2019 - hal.science
Problems tackled by researchers and data scientists in aviation and air traffic management
(ATM) require manipulating large amounts of data representing trajectories, flight …
(ATM) require manipulating large amounts of data representing trajectories, flight …
CAE: Contextual auto-encoder for multivariate time-series anomaly detection in air transportation
Abstract The Automatic Dependent Surveillance-Broadcast protocol is one of the latest
compulsory advances in air surveillance. While it supports the tracking of the ever-growing …
compulsory advances in air surveillance. While it supports the tracking of the ever-growing …
Deep trajectory clustering with autoencoders
X Olive, L Basora, B Viry, R Alligier - ICRAT 2020, 9th …, 2020 - enac.hal.science
Identification and characterisation of air traffic flows is an important research topic with many
applications areas including decision-making support tools, airspace design or traffic flow …
applications areas including decision-making support tools, airspace design or traffic flow …
Detection and identification of significant events in historical aircraft trajectory data
X Olive, L Basora - Transportation Research Part C: Emerging …, 2020 - Elsevier
A large amount of data is produced every day by stakeholders of the Air Traffic Management
(ATM) system, in particular airline operators, airports, and air navigation service providers …
(ATM) system, in particular airline operators, airports, and air navigation service providers …
Trajectory clustering within the terminal airspace utilizing a weighted distance function
To support efforts to modernize aviation systems to be safer and more efficient, high-
precision trajectory prediction and robust anomaly detection methods are required. The …
precision trajectory prediction and robust anomaly detection methods are required. The …
A data analytics framework for anomaly detection in flight operations
LC e Silva, MCR Murça - Journal of Air Transport Management, 2023 - Elsevier
In the air transport system, there has been a continuous effort to develop policies, tools, and
methodologies that increase and standardize safety levels across the entire commercial …
methodologies that increase and standardize safety levels across the entire commercial …
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 …
incident and accident investigation, and fault detection has gained traction among the …
Gaussian Mixture Model-Based online anomaly detection for vectored area navigation arrivals
Identifying anomalous flight trajectories is crucial in airspace operations, as they can
potentially lead to safety risks. One of the challenges in identifying abnormal aircraft …
potentially lead to safety risks. One of the challenges in identifying abnormal aircraft …