Conceptualization and Application of Deep Learning and Applied Statistics for Flight Plan Recommendation

Abstract

The Air Forces Pilot Training Next (PTN) program seeks a more efficient pilot training environment emphasizing the use of virtual reality flight simulators alongside periodic real aircraft experience. The PTN program wants to accelerate the training pace and progress in undergraduate pilot training compared to traditional undergraduate pilot training. Currently, instructor pilots spend excessive time planning and scheduling flights. This research focuses on methods to auto-generate the planning of in-flight events using hybrid filtering and deep learning techniques. The resulting approach captures temporal trends of user-specific and program-wide student performance to recommend a feasible set of graded flight events for evaluation in a students next training exercise to improve their progress toward fully qualified status.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2020
Accession Number
AD1101487

Entities

People

  • Nicholas C. Forrest

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Energy and Power Technologies
  • Ground and Sea Platforms
  • Human Systems
  • Weapons Technologies

DTIC Thesaurus Topics

  • Air Force
  • Artificial Intelligence
  • Artificial Intelligence Software
  • Computational Science
  • Computer Languages
  • Computers
  • Data Analysis
  • Data Mining
  • Department Of Defense
  • Flight
  • Flight Simulators
  • Flight Training
  • Information Science
  • National Security
  • Neural Networks
  • Recurrent Neural Networks
  • Students

Readers

  • Aviation Science / Aeronautics.
  • Neural Network Machine Learning.
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks