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Cited by 254Anomaly Detection Techniques and ApplicationsAir Traffic Management and OptimizationFault Detection and Control Systems

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

Li, Lishuai, Hansman, R. John, Palacios, Rafael, Welsch, Roy·2016·Transportation Research Part C: Emerging Technologies
DOI 10.1016/j.trc.2016.01.007
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Crossref · 10.1016/j.trc.2016.01.007

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  • AI algorithms can be used to detect fraudulent activity, such as credit card fraud or identity theft, helping airlines to reduce financial losses.

    “AI algorithms can be used to detect fraudulent activity, such as credit card fraud or identity theft, helping airlines to reduce financial losses [122] .”

    From Artificial intelligence, machine learning and deep learning in advanced robotics, a review (2023) · cites this paper as [122]

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Authors
Li, L., Hansman, R. J., Palacios, R., & Welsch, R.
Affiliations
  • City University of Hong Kong (HK)
  • Massachusetts Institute of Technology (US)
  • Universidad Pontificia Comillas (ES)
Corresponding author
Li, Lishuai
ORCID
Venue
Transportation Research Part C: Emerging Technologies
Publisher
Elsevier BV
Published
2016-03
Volume
64
Pages
45-57
ISSN
0968-090X (ISSN-L)
DOI
10.1016/j.trc.2016.01.007
OpenAlex
W2268212270
Cited by
254
References
0
Citations by year
2026: 24 · 2025: 34 · 2024: 27 · 2023: 38 · 2022: 40 · 2021: 35 · 2020: 21 · 2019: 16 · 2018: 16 · 2017: 3
FWCI
8.73
Type
journal article
Language
en
Open access
closed
Licence
www.elsevier.com/tdm/userlicense/1.0/ (tdm)
Locations
  • Transportation Research Part C Emerging Technologies (publishedVersion)
  • Comillas Repository (Comillas Pontifical University) (submittedVersion)
Funders
  • Federal Aviation Administration (FAA 11-G-016)
  • National Aeronautics and Space Administration (NNA06CN23A)
  • City University of Hong Kong Start-up (7200418)
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Anomaly Detection Techniques and Applications
  • Physical Sciences › Engineering › Aerospace Engineering › Air Traffic Management and Optimization
  • Physical Sciences › Engineering › Control and Systems Engineering › Fault Detection and Control Systems
Keywords
anomaly detection, Gaussian mixture model, aviation safety, flight data analysis, unsupervised clustering

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