The Prediction Algorithm for the Landing Craft Air Cushion Vehicle (LCAC) Selection System,

Abstract

This paper explains the prediction algorithm used by the Landing Craft Air Cushion Vehicle (LCAC) selection system. Five variables from a psychomotor test battery were combined to form a composite score. This composite score was then compared to a threshold score. If a candidate for an LCAC crew position achieved a composite score higher than the threshold score, that candidate was predicted to pass Phase I of LCAC training. Likewise, if a candidate scored lower than the threshold score he was predicted to fail training. The threshold score was determined by Statistical Decision Theory as interpreted from the Bayesian approach. Examples are given showing how the threshold scores can change as a function of the prior probabilities of pass or fail and the values attached to making correct and incorrect predictions.

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 1996
Accession Number
ADA320790

Entities

People

  • David J. Blower

Organizations

  • Naval Aerospace Medical Research Laboratory

Tags

Communities of Interest

  • Biomedical
  • Human Systems

DTIC Thesaurus Topics

  • Air Cushion Vehicles
  • Algorithms
  • Attrition
  • Bayesian Networks
  • Biomedical Research
  • Composite Materials
  • Data Science
  • Decision Theory
  • Discriminant Analysis
  • Information Science
  • Landing Craft
  • Materials
  • Mathematical Models
  • Probability
  • Statistical Decision Theory
  • Students
  • Vehicles

Readers

  • Computational Modeling and Simulation
  • Naval Architecture and Marine Engineering.
  • Psychometric Testing or Psychological Assessment.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference