Paper Info
Title
A comparison of methodologies for fuzzy expert system creation--application to arrhythmic beat classification.
Abstract
In this work, three different methodologies for fuzzy expert systems creation are compared: a well-known neuro-fuzzy approach, a knowledge-based approach and a novel methodology, based on rule-extraction. The adaptive neuro-fuzzy information system (ANFIS) is used to automatically generate a fuzzy expert system. In the knowledge-based approach and the rule-extraction methodology, the idea is to start with a model described by crisp rules, provided by medical experts in the first case or extracted using data mining techniques in the second, and then to transform them into a set of fuzzy rules, creating a fuzzy model. In either case, the adjustment of the model's parameters is performed via a stochastic global optimization procedure. All three approaches are applied to a medical domain problem, the cardiac arrhythmic beat classification. The ability to interpret the decisions made from the created fuzzy expert systems is a major advantage compared to other "black box" approaches.
Year
DOI
Venue
2006
10.1109/IEMBS.2006.260565
EMBC
Keywords
DocType
Volume
knowledge based systems,decision tree,knowledge base,data mining,cardiology,neuro fuzzy,global optimization,information system,decision trees
Conference
1
ISSN
Citations 
PageRank 
1557-170X
0
0.34
References 
Authors
10
3
Name
Order
Citations
PageRank
Markos G Tsipouras1283.95
Themis P Exarchos274.66
Dimitrios I Fotiadis34914.82