Accession Number:

ADA457596

Title:

Analyzing Divisia Rules Extracted from a Feedforward Neural Network

Descriptive Note:

Corporate Author:

AIR FORCE RESEARCH LAB WRIGHT-PATTERSON AFB OH HUMAN EFFECTIVENESS DIRECTORATE

Personal Author(s):

Report Date:

2006-03-01

Pagination or Media Count:

10.0

Abstract:

This paper introduces a mechanism for generating a series of rules that characterize the money-price relationship, defined as the relationship between the rate of growth of the money supply and inflation. Division component data is used to train a selection of candidate feedforward neural networks. The selected network is mined for rules, expressed in human-readable and machine-executable form. The rule and network accuracy are compared, and expert commentary is made on the readability and reliability of the extracted rule set. The ultimate goal of this research is to produce rules that meaningfully and accurately describe inflation in terms of Division component dataset.

Subject Categories:

  • Computer Programming and Software
  • Cybernetics

Distribution Statement:

APPROVED FOR PUBLIC RELEASE