Title :
Incremental induction of fuzzy classification rules
Author :
Bouchachia, Abdelhamid
Author_Institution :
Dept. of Inf., Univ. of Klagenfurt, Klagenfurt
fDate :
March 30 2009-April 2 2009
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;
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
DOI :
10.1109/ESDIS.2009.4938996
