Paper Info
Title
Encoding Fuzzy Diagnosis Rules As Optimisation Problems
Abstract
This paper discusses how to encode fuzzy knowledge bases for diagnostic tasks (i.e., list of symptoms produced by each fault, in linguistic terms described by fuzzy sets) as constrained optimisation problems. The proposed setting allows more flexibility than some fuzzy-logic inference rulebases in the specification of the diagnostic rules in a transparent, user-understandable way (in a first approximation, rules map to zeros and ones in a matrix), using widely-known techniques such as linear and quadratic programming.
Year
DOI
Venue
2006
10.1007/978-3-540-79142-3_5
ICINCO-ICSO
Keywords
Field
DocType
fault detection and diagnosis, fuzzy mathematical programming, approximate reasoning, optimisation
Data mining,Neuro-fuzzy,Fuzzy classification,Defuzzification,Fuzzy set operations,Control engineering,Fuzzy set,Theoretical computer science,Adaptive neuro fuzzy inference system,Fuzzy number,Fuzzy associative matrix,Mathematics
Conference
Citations 
PageRank 
References 
0
0.34
10
Authors
4
Name
Order
Citations
PageRank
A. Sala156233.44
Alicia Esparza2222.70
Carlos Ariño310910.89
Jose V. Roig400.34