Accession Number:

AD1101487

Title:

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

Descriptive Note:

Technical Report,01 Sep 2018,01 Mar 2020

Corporate Author:

AIR FORCE INSTITUTE OF TECHNOLOGY WRIGHT-PATTERSON AFB OH WRIGHT-PATTERSON AFB United States

Personal Author(s):

Report Date:

2020-03-01

Pagination or Media Count:

143.0

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.

Subject Categories:

  • Military Operations, Strategy and Tactics

Distribution Statement:

APPROVED FOR PUBLIC RELEASE