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Multiclass Anomaly Detection in Flight Data Using Semi-Supervised Explainable Deep Learning Model
- Source :
- Journal of Aerospace Information Systems. 19:83-97
- Publication Year :
- 2022
- Publisher :
- American Institute of Aeronautics and Astronautics (AIAA), 2022.
-
Abstract
- The identification of precursors to safety incidents in aviation data is a crucial task, yet extremely challenging. The main approach in practice leverages domain expertise to define expected toler...
- Subjects :
- business.industry
Computer science
Deep learning
Aerospace Engineering
Machine learning
computer.software_genre
Computer Science Applications
Task (project management)
Support vector machine
National Airspace System
Identification (information)
Subject-matter expert
Recurrent neural network
Anomaly detection
Artificial intelligence
Electrical and Electronic Engineering
business
computer
Subjects
Details
- ISSN :
- 23273097
- Volume :
- 19
- Database :
- OpenAIRE
- Journal :
- Journal of Aerospace Information Systems
- Accession number :
- edsair.doi...........9e19871926730813275f21603e9bb37d
- Full Text :
- https://doi.org/10.2514/1.i010959