Paper Info
Title
Genetic Learning Of Fuzzy Rule-Based Classification Systems Cooperating With Fuzzy Reasoning Methods
Abstract
In this paper, we present a multistage genetic learning process for obtaining linguistic fuzzy rule-based classification systems that integrates fuzzy reasoning methods cooperating with the fuzzy rule base and learns the best set of linguistic hedges for the linguistic variable terms. We show the application of the genetic learning process to two well known sample bases, and compare the results with those obtained from different learning algorithms. The results show the good behavior of the proposed method, which maintains the linguistic description of the fuzzy rules. (C) 1998 John Wiley & Sons, Inc.
Year
DOI
Venue
1998
10.1002/(SICI)1098-111X(199810/11)13:10/11<1025::AID-INT9>3.0.CO;2-N
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
Keywords
Field
DocType
classification system,rule based,genetics
Neuro-fuzzy,Fuzzy classification,Defuzzification,Fuzzy set operations,Fuzzy logic,Artificial intelligence,Fuzzy number,Type-2 fuzzy sets and systems,Machine learning,Mathematics,Fuzzy rule
Journal
Volume
Issue
ISSN
13
10-11
0884-8173
Citations 
PageRank 
References 
60
3.92
17
Authors
3
Name
Order
Citations
PageRank
Oscar Cordon1759.21
María José Jesús254734.73
Francisco Herrera3273911168.49