DocumentCode :
3494496
Title :
A new neuro-fuzzy system for efficient ATM traffic control
Author :
Custodio, Jorge J. ; Tascón, Manuel ; Merino, Manuel ; Dimitriadis, Yannis A.
Author_Institution :
Dept. of Signal Theory, Valladolid Univ., Spain
Volume :
2
fYear :
1999
fDate :
1999
Firstpage :
964
Abstract :
We present and apply the fuzzy adaptive system ART-based (FasArt) neuro-fuzzy system to the problems of connection admission control (CAC) and usage parameter control (UPC). FasArt provides the advantages of both a fuzzy logic system (simplicity and interpretability of fuzzy rules) and an ART-based neural network (fast, stable and incremental learning). An extensive experimental work in the Ptolemy simulation environment is presented, together with an analysis of system performance. Besides the general fine properties of FasArt, a superior performance was confirmed in comparison to other conventional, fuzzy or neural systems in the UPC problem, with respect to selectiveness, low response time and false alarm probability. On the other hand, performance in the CAC problem was satisfactory, as far as cell loss rate and link usage are concerned, especially when FasArt was employed as a function identification system
Keywords :
asynchronous transfer mode; ART-neural network; ATM traffic control; FasArt; cell loss rate; connection admission control; fuzzy adaptive system; fuzzy neural networks; incremental learning; link usage; usage parameter control;
fLanguage :
English
Publisher :
iet
Conference_Titel :
Artificial Neural Networks, 1999. ICANN 99. Ninth International Conference on (Conf. Publ. No. 470)
Conference_Location :
Edinburgh
ISSN :
0537-9989
Print_ISBN :
0-85296-721-7
Type :
conf
DOI :
10.1049/cp:19991237
Filename :
818062
Link To Document :
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