Optimizing ship air-defense evaluation model using simulation and inductive learning
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Authors
Lo, Chang-yun
Subjects
Ship air-defense simulation model
Inductive learning
ID3
Inductive learning
ID3
Advisors
Lee, Yuh-jeng
Date of Issue
1991-03
Date
March 1991
Publisher
Monterey, California. Naval Postgraduate School
Language
en_US
Abstract
This thesis presents an effective method to integrate simulation modeling with inductive learning the 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 weapons operations. In addition, results 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.
Type
Thesis
Description
Series/Report No
Department
Operations Research (OR)
Organization
Naval Postgraduate School
Identifiers
NPS Report Number
Sponsors
Funding
Format
74 p.
Citation
Distribution Statement
Approved for public release; distribution is unlimited.
Rights
Copyright is reserved by the copyright owner