Using Deep Learning to Predict Unstable Approaches for General Aviation Aircraft

Abstract

No AccessTechnical NotesUsing Deep Learning to Predict Unstable Approaches for General Aviation AircraftTanish Jain, Shlok Misra and Dothang TruongTanish Jain https://orcid.org/0000-0002-0571-4948Stanford University, Stanford, California 94305*Graduate Researcher.Search for more papers by this author, Shlok Misra https://orcid.org/0000-0002-3976-5217Embry-Riddle Aeronautical University, Daytona Beach, Florida 32114*Graduate Researcher.Search for more papers by this author and Dothang Truong https://orcid.org/0000-0002-6900-6916Embry-Riddle Aeronautical University, Daytona Beach, Florida 32114†Professor, School of Graduate Studies.Search for more papers by this authorPublished Online:25 Oct 2022https://doi.org/10.2514/1.I011132SectionsRead Now ToolsAdd to favoritesDownload citationTrack citations About References [1] Implementation Plan 2018-19, N., Aircraft Owners and Pilots Association 30th Joseph T. 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TopicsAeronauticsAircraft Operations and TechnologyAircraftsArtificial IntelligenceArtificial Neural NetworkAviationAviation Accidents and IncidentsAviation MeteorologyAviation SafetyCivil AviationComputing SystemComputing and InformaticsComputing, Information, and CommunicationData ScienceHistory of AviationMachine Learning KeywordsGeneral AviationCommercial AircraftRecurrent Neural NetworkMachine LearningAviation AccidentsFlight Operations Quality AssuranceMeteorological Aerodrome ReportPDF Received2 April 2022Accepted5 September 2022Published online25 October 2022