Accession Number:

AD1158586

Title:

Improving the Digital Aviation Readiness Technology Engine (DARTE) with Temporal Pattern Attention Mechanisms and Hyper-Deep Ensembles

Descriptive Note:

[Technical Report, Final Report]

Corporate Author:

NAVAL INFORMATION WARFARE CENTER PACIFIC SAN DIEGO CA

Report Date:

2022-02-01

Pagination or Media Count:

36

Abstract:

The Digital Aviation Readiness Technology Engine DARTE provides unprecedented predictive readiness capabilities for the Naval FA-18 fleet. DARTE focuses on discovering actionable insights in relation to predicting two key readiness metrics the number of mission capable MC aircraft and flight hours. Recent DARTE efforts have focused on improvements including the adoption of cutting edge artificial intelligence AI and deep learning techniques such as temporal pattern attention mechanism-enhanced long short-term memory LSTMA networks, hyper-deep ensembles for enhanced performance, and improved uncertainty estimation and robustness. Hyper-deep ensembles and attention mechanisms have been shown to provide state-of-the art results in industry and academia. Furthermore, their improved uncertainty estimation provides decision makers with an increased level of confidence that allows for better, smarter decisions.

Subject Categories:

  • Military Aircraft Operations
  • Cybernetics

Distribution Statement:

[A, Approved For Public Release]