Conceptual Models of Unit Performance

Abstract

This report summarizes work testing the usefulness of neural network models for measuring and predicting Army unit performance in settings such as the National Training Center. A back-propagation neural network model was developed and trained from wargaming simulation. Results suggest that such a model can train to recognize unit success and failure in simulated engagements. Further work will require access to clean, large, data sets, such as those available from SIMNET. In addition, an expert-based preprocessor is suggested as a useful approach to implementing a model.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1991
Accession Number
ADA232743

Entities

People

  • Freeman Marvin
  • Jeffrey S. Mandel
  • Kathryn B. Laskey
  • Stuart H. Rakoff

Tags

Communities of Interest

  • Energy and Power Technologies
  • Ground and Sea Platforms
  • Human Systems
  • Weapons Technologies

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Artificial Intelligence Software
  • Classification
  • Computational Science
  • Computer Programming
  • Computer Programs
  • Computers
  • Data Sets
  • Doctrine
  • Economic Systems
  • Instructions
  • Mathematical Models
  • Neural Networks
  • Simulations
  • Task Forces
  • Training
  • War Games

Readers

  • Computational Modeling and Simulation
  • Military Training and Readiness Simulation
  • Neural Network Machine Learning.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Neural Networks