DocumentCode :
3385167
Title :
A supervised fuzzy clustering for Radial Basis Function Neural Networks training
Author :
Tagliaferri, R. ; Staiano, A. ; Scala, D.
Author_Institution :
DMI, Salerno Univ., Baronissi, Italy
Volume :
3
fYear :
2001
fDate :
25-28 July 2001
Firstpage :
1804
Abstract :
In this paper we present a new learning algorithm for radial basis function neural networks (RBFNN´s) based on a supervised fuzzy clustering technique. Our methodology follows the conditional fuzzy clustering presented by W. Pedrycz (1998) and permits to obtain a completely automatic clustering, where data agglomeration is based on both input and output pattern values
Keywords :
fuzzy logic; learning (artificial intelligence); pattern clustering; radial basis function networks; automatic clustering; conditional fuzzy clustering; data agglomeration; learning algorithm; radial basis function neural networks training; supervised fuzzy clustering; Clustering algorithms; Clustering methods; Estimation theory; Function approximation; Fuzzy neural networks; Interpolation; Neural networks; Prototypes; Radial basis function networks; Vehicles;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
IFSA World Congress and 20th NAFIPS International Conference, 2001. Joint 9th
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-7078-3
Type :
conf
DOI :
10.1109/NAFIPS.2001.943826
Filename :
943826
Link To Document :
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