DocumentCode
3428739
Title
Incremental induction of fuzzy classification rules
Author
Bouchachia, Abdelhamid
Author_Institution
Dept. of Inf., Univ. of Klagenfurt, Klagenfurt
fYear
2009
fDate
March 30 2009-April 2 2009
Firstpage
32
Lastpage
39
Abstract
The present paper presents an incremental fuzzy rule based system for classification purposes. Relying on fuzzy min-max neural networks, the present paper shows how fuzzy rules can be continuously online generated to meet the requirements of non-stationary dynamic environments. Simulation results are reported to show the effectiveness of the proposed approach.
Keywords
fuzzy neural nets; knowledge based systems; learning (artificial intelligence); fuzzy classification rules; fuzzy min-max neural networks; incremental fuzzy rule based system; incremental induction; nonstationary dynamic environments; Application software; Data mining; Fuzzy neural networks; Fuzzy systems; Induction generators; Knowledge based systems; Machine learning; Machinery; Neural networks; Stability;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolving and Self-Developing Intelligent Systems, 2009. ESDIS '09. IEEE Workshop on
Conference_Location
Nashville, TN
Print_ISBN
978-1-4244-2754-3
Type
conf
DOI
10.1109/ESDIS.2009.4938996
Filename
4938996
Link To Document