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Accession Number:
AD1085789
Title:
Predicting FA-18 Squadron Readiness and Quarterly Flight Hour Execution Using Machine Learning
Corporate Author:
Naval Information Warfare Center Pacific San Diego United States
Report Date:
2019-12-01
Abstract:
Given manning-training-equipment datasets from Naval FA-18 squadrons, a machine learning model for determining the monthly mean number of mission capable jets per squadron is created. This model is then extended and used as an input to create an ensemble of models determining the flight hour execution of a squadron over a three-month period. The ensemble of models is then used to predict squadron performance and readiness, and can correctly classify a squadrons future performance with 75 accuracy 90-days in advance.
Descriptive Note:
Technical Report,01 Jan 2018,01 Jan 2019
Supplementary Note:
01 Jan 0001, 01 Jan 0001, This reports content represents work performed under Space and Naval Warfare Systems Center Pacific (SSC Pacific). SSC Pacific formally changed its name to Naval Information Warfare Center Pacific (NIWC Pacific) in February 2019.
Pages:
0050
Distribution Statement:
Approved For Public Release;
File Size:
5.51MB
