A comprehensive survey of clustering algorithms: State-of-the-art machine learning applications, taxonomy, challenges, and future research prospects

AE Ezugwu, AM Ikotun, OO Oyelade… - … Applications of Artificial …, 2022 - Elsevier
Clustering is an essential tool in data mining research and applications. It is the subject of
active research in many fields of study, such as computer science, data science, statistics …

Recent advances in anomaly detection methods applied to aviation

L Basora, X Olive, T Dubot - Aerospace, 2019 - mdpi.com
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 …

Anomaly detection via a Gaussian Mixture Model for flight operation and safety monitoring

L Li, RJ Hansman, R Palacios, R Welsch - Transportation Research Part C …, 2016 - Elsevier
Safety is key to civil aviation. To further improve its already respectable safety records, the
airline industry is transitioning towards a proactive approach which anticipates and mitigates …

Unsupervised anomaly detection in flight data using convolutional variational auto-encoder

M Memarzadeh, B Matthews, I Avrekh - Aerospace, 2020 - mdpi.com
The modern National Airspace System (NAS) is an extremely safe system and the aviation
industry has experienced a steady decrease in fatalities over the years. This is in part due …

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] From Twitter to traffic predictor: Next-day morning traffic prediction using social media data

W Yao, S Qian - Transportation research part C: emerging technologies, 2021 - Elsevier
The effectiveness of traditional traffic prediction methods, such as autoregressive or spatio-
temporal models, is often extremely limited when forecasting traffic dynamics in early …

Real-time anomaly detection framework using a support vector regression for the safety monitoring of commercial aircraft

H Lee, G Li, A Rai, A Chattopadhyay - Advanced Engineering Informatics, 2020 - Elsevier
The development of an automated health monitoring framework is critical for aviation system
safety, especially considering the expected increase in air traffic over the next decade …

Towards online prediction of safety-critical landing metrics in aviation using supervised machine learning

TG Puranik, N Rodriguez, DN Mavris - Transportation Research Part C …, 2020 - Elsevier
In recent years, due to the increased availability of data and improvements in computing
power, application of machine learning techniques to various aviation safety problems for …

Anomaly detection in general-aviation operations using energy metrics and flight-data records

TG Puranik, DN Mavris - Journal of Aerospace Information Systems, 2018 - arc.aiaa.org
Among the operations in the general-aviation community, one of the most important
objectives is to improve safety across all flight regimes. Flight-data-monitoring or flight …

Trajectory pattern identification and classification for real-time air traffic applications in Area Navigation terminal airspace

C Deng, HC Choi, H Park, I Hwang - Transportation Research Part C …, 2022 - Elsevier
In order to address the continuing growth of demands on airspace capacity, various
navigation methods have been developed such as Area Navigation (RNAV), which allows …