Accession Number:

ADA224297

Title:

Quantitative Knowledge Acquisition for Expert Systems

Descriptive Note:

Technical interim rept.

Corporate Author:

PRINCETON UNIV NJ DEPT OF MECHANICAL AND AEROSPACE ENGINEERING

Report Date:

1990-06-01

Pagination or Media Count:

11.0

Abstract:

A common problem in the design of expert systems is the definition of rules from data obtained in system operation or simulation. While it is relatively easy to collect data and to log the comments of human operators engaged in experiments, generalizing such information to a set of rules has not previously been a straightforward task. This paper presents a statistical method for generating rule bases from numerical data, motivated by an example based on aircraft navigation with multiple sensors. The specific objective is to design an expert system that selects a satisfactory suite of measurements from a dissimilar, redundant set, given an arbitrary navigation geometry and possible sensor failures. This paper describes the systematic development of a Navigation Sensor Management NSM Expert System from Kalman Filter covariance data. The development method invokes two statistical techniques Analysis of Variance ANOVA and the ID3 algorithm. rrh

Subject Categories:

  • Air Navigation and Guidance
  • Human Factors Engineering and Man Machine Systems

Distribution Statement:

APPROVED FOR PUBLIC RELEASE