An improved technique for applying fuzzy logic in a model-based diagnostics reasoner

Author

Bearse, Timothy M. ; Lynch, Michael L.

Author_Institution

Naval Undersea Warfare Center Div., Newport, RI, USA

Volume

3

fYear

1999

fDate

1999

Firstpage

151

Abstract

The authors apply an improved technique based on fuzzy logic to fulfill the requirement to compute a fault hypothesis in a model-based diagnostic reasoner. The primary focus of the paper is to extend previous work and illustrate the use of the improved algorithm. The paper deals primarily with two types of uncertainty: test outcome uncertainty and inference uncertainty. The issue of conflict detection and conclusion rehabilitation is addressed. This proposed fuzzy logic approach uses the confidence parameters defined in the IEEE 1232: Artificial Intelligence Exchange and Service Tie to All Test Environments (AI-ESTATE) standard to provide a robust reasoning under uncertainty capability

Keywords

IEEE standards; diagnostic reasoning; fuzzy logic; model-based reasoning; uncertainty handling; AI-ESTATE; IEEE 1232 standard; artificial intelligence; conclusion rehabilitation; confidence parameters; conflict detection; fault hypothesis; fuzzy logic; inference uncertainty; model-based diagnostics reasoner; robust reasoning; test environments; test outcome uncertainty; Artificial intelligence; Fuzzy logic; Fuzzy sets; Inference algorithms; Logic testing; Measurement uncertainty; Military computing; Robustness; Set theory; System testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Aerospace Conference, 1999. Proceedings. 1999 IEEE

Conference_Location

Snowmass at Aspen, CO

Print_ISBN

0-7803-5425-7

Type

conf

DOI

10.1109/AERO.1999.789774

Filename

789774