DocumentCode :
2387698
Title :
Some properties on a class of neuro-fuzzy learning algorithms
Author :
Yan Shi ; Mizumoto, M.
fYear :
2004
fDate :
26-31 Aug. 2004
Firstpage :
319
Lastpage :
322
Abstract :
In this paper, we try to analyze two kind; of conventional neuro-fuzzy learning algorithms, which are widely used in recent fuzzy applications for tuning fuzzy rules, and give a summarization of their properties. Some of these properties show that uses of the conventional neuro-fuzzy learning algorithms are sometimes dillicult or inconvenient for constructing an optimal fuzzy system model in practical fuzzy applications.
Keywords :
Algorithm design and analysis; Fuzzy reasoning; Fuzzy systems; Gaussian processes; Humans; Inference algorithms; Neural networks; Space technology; Training data; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Mechatronics and Automation, 2004. Proceedings. 2004 International Conference on
Conference_Location :
Chengdu, China
Print_ISBN :
0-7803-8748-1
Type :
conf
DOI :
10.1109/ICIMA.2004.1384212
Filename :
1384212
Link To Document :
بازگشت