An Update to the Landing Air Craft Cushion (LCAC) Navigator Selection System Prediction Algorithm

Abstract

This report updates the status of the Landing Craft Air Cushion (LCAC) Navigator Selection System prediction algorithm. The last revision took place at the end of 1997. With the receipt of new training data, the prediction algorithm was changed in June 2000 to take advantage of this new data. Some rough estimates of the new attrition rate and the rejection rate due to the selection system may be made on the basis of the new data. The attrition rate is estimated as 17.24% and the rejection rate as 36.96%. The failure rate during training appears to be about 39.13%. If the rejection rate of about 37% is acceptable, then the LCAC Navigator Selection System can reduce the attrition rate from around 40% to around 17%. Of course, these estimates are based on rather small numbers and therefore are subject to substantial revision as more data accrues. The prediction of a success or failure for any given candidate by the LCAC Navigator Selection System is built on the foundation of statistical decision theory (SDT). The selection system is trying to make a decision about a candidate whose composite score on the test battery is known, but whose training outcome is unknown. There is then, by definition, some uncertainty about the training outcome for this candidate. Uncertainty and the problem of making decisions in an uncertain world is the province of probability theory and SDT. The only mathematically self-consistent way that has been found to treat uncertainty is through probability theory. From the basic axioms of probability theory one is able to construct an appealing approach to uncertainty called the Bayesian approach. One of the core concepts within the Bayesian approach is the predictive probability density function. This paper presents some numerical examples of how a Bayesian predictive density can be calculated for the LCAC Navigator Selection System.

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Document Details

Document Type
Technical Report
Publication Date
Dec 15, 2000
Accession Number
ADA531672

Entities

People

  • D.j. Blower

Organizations

  • Naval Aerospace Medical Research Laboratory

Tags

Communities of Interest

  • Biomedical
  • C4I
  • Human Systems

DTIC Thesaurus Topics

  • Aircrafts
  • Algorithms
  • Attrition
  • Basic Programming Language
  • Bayesian Networks
  • Computer Programs
  • Databases
  • Decision Theory
  • Discriminant Analysis
  • Landing Craft
  • Normal Distribution
  • Personnel Management
  • Personnel Selection
  • Probability
  • Probability Density Functions
  • Probability Distributions
  • Statistical Decision Theory

Readers

  • Aviation Science / Aeronautics.
  • Statistical inference.
  • Theoretical Analysis.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference