Accession Number:

ADA242946

Title:

Optimizing Ship Air-Defense Evaluation Model Using Simulation and Inductive Learning

Descriptive Note:

Master's thesis,

Corporate Author:

NAVAL POSTGRADUATE SCHOOL MONTEREY CA

Personal Author(s):

Report Date:

1991-03-01

Pagination or Media Count:

82.0

Abstract:

This thesis presents an effective method to integrate simulation modeling with inductive learning to analyze ship air-defense combat scenarios. By combining the use of inductive learning with simulation, we are able to discover rules in a ship air-defense evaluation model about the optimal weapon assignments that we might not be aware of or could not express clearly. This approach can also perform sensitivity analysis in identifying variables that are critical for certain weapon operations. In addition, results obtained from inductive learning, as represented in the format of decision trees, are easy for a human user to understand, maintain, and adopt for other use.

Subject Categories:

  • Computer Programming and Software
  • Antimissile Defense Systems
  • Antiaircraft Defense Systems
  • Naval Surface Warfare

Distribution Statement:

APPROVED FOR PUBLIC RELEASE