Modeling How Individual Enities React to Indirect Fire

Abstract

Current Army models and simulations provide limited representation of the actions and behaviors of the individual combatant (Soldier, Sailor, Marine, or Airman). As the Army transforms into the Future Force, more emphasis is being placed on modeling the actions and behaviors of the individual combatant. The Training and Doctrine Command Analysis Center Monterey has initiated the Individual Combatant Research Project. One research area is modeling how individual entities react to indirect fire, which is the focus of this thesis. From a study of both historical examples and current U.S. Army doctrine, we derived the input factors and responses. We selected the most significant input factors and derived a general model to represent this phenomenon. From the general model we derived a specific model that we implemented as a behavior rule using the Combined Arms Analysis Tool for the 21st Century, CXXI. In order to determine the effectiveness of the model, we used the face validation method. Our data analysis consisted of a two-sample t-test, a Mann-Whitney test, and a two-way analysis of variance. From our analysis we concluded that implementation of our model in CXXI was an improvement that made CXXI more realistic and functional.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 2004
Accession Number
ADA424823

Entities

People

  • D. B. Streater

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Human Systems
  • Weapons Technologies

DTIC Thesaurus Topics

  • Analysis Of Variance
  • Combat Operations
  • Combat Readiness
  • Computer Programs
  • Data Analysis
  • Data Science
  • Databases
  • Doctrine
  • Howitzers
  • Indirect Fire
  • Information Science
  • Iraqi-War
  • Military Science
  • Military Training
  • Operations Research
  • Training
  • Warfare

Readers

  • Computational Modeling and Simulation
  • Joint Military Operations and Doctrine.
  • Military Training and Readiness Simulation

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference