Comparison of a Back Propagation Artificial Neural Network Model with a Linear Regression Model for Personnel Selection

Abstract

This exploratory research examined the usefulness of an Artificial Neural Network-Back Propagation (ANN-BP) model predicting dichotomous criteria in personnel selection. The results are quite encouraging. Under a wide variety of circumstances, the ANN-BP model was superior to the Ordinary Least-Squares- Linear Regression (OLS-LR) model in predicting curvilinear relationships. (My once was OLS-LR superior. When the underlying relationship was linear, there were no significant differences. This is somewhat remarkable, given that the OLS-LR model was designed to perform optimally in the linear case. Artificial neural networks, Back propagation, Personnel selection.

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Document Details

Document Type
Technical Report
Publication Date
May 01, 1994
Accession Number
ADA280023

Entities

People

  • C. A. Wilkins
  • W. A. Sands

Organizations

  • Bureau of Naval Personnel

Tags

DTIC Thesaurus Topics

  • Abstracts
  • Administrative Personnel
  • Air Force
  • Air Force Personnel
  • Computer Programs
  • Computers
  • Data Science
  • Data Sets
  • Management Personnel
  • Military Personnel
  • Military Research
  • Neural Networks
  • Personnel Management
  • Personnel Selection
  • Self Organizing Systems
  • Standards
  • Statistical Analysis

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Neural Network Machine Learning.
  • Psychometric Testing or Psychological Assessment.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms
  • AI & ML - Neural Networks