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Titolo:
ADAPTIVE TREE-STRUCTURED SELF-GENERATING RADIAL BASIS FUNCTION NETWORK AND ITS PERFORMANCE EVALUATION
Autore:
WATANABE M; KUWATA K; KATAYAMA R;
Indirizzi:
SANYO ELECT CO LTD,HYPERMEDIA RES CTR,1-18-13 HASHIRIDANI OSAKA 573 JAPAN
Titolo Testata:
International journal of approximate reasoning
fascicolo: 4, volume: 13, anno: 1995,
pagine: 303 - 326
SICI:
0888-613X(1995)13:4<303:ATSRBF>2.0.ZU;2-P
Fonte:
ISI
Lingua:
ENG
Keywords:
ADAPTIVE FREE STRUCTURE; RADIAL BASIS FUNCTION; SELF-GENERATING RBF; MAXIMUM ABSOLUTE ERROR SELECTION METHOD; NONLINEAR IDENTIFICATION;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
CompuMath Citation Index
Science Citation Index Expanded
Science Citation Index Expanded
Citazioni:
15
Recensione:
Indirizzi per estratti:
Citazione:
M. Watanabe et al., "ADAPTIVE TREE-STRUCTURED SELF-GENERATING RADIAL BASIS FUNCTION NETWORK AND ITS PERFORMANCE EVALUATION", International journal of approximate reasoning, 13(4), 1995, pp. 303-326

Abstract

Several algorithms have been proposed to identify a large scale system, such as the neuro-fuzzy GMDH, and the fuzzy modeling using a fuzzy neural network. As another approach, Sanger proposed a tree-structuredadaptive network But in Sanger's network, it is not clear how to determine the initial disposition of bases and the number of bases in eachsubtree. We propose a nonlinear modeling method called the adaptive tree-structured self-generating radial basis function network (A Tree-RBFN). In A Tree-RBFN, we take the maximum absolute error (MAE) selection method in order to improve Sanger's model. We combine Sanger's tree-structured adaptive network for an overall model structure with the MAE selection method for a subtree identification problem. In ATree-RBFN, the tuning parameters are not only the coefficients but also the centers and widths of bases, and a subtree can be generated under all leaf nodes. Then, the input-output data can be divided into the trainingdata set and the checking data set, and an element of inputs in each subtree is selected according to the corresponding aror value from thechecking data set. We also demonstrate the effectiveness of the proposed method by solving several numerical examples.

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Documento generato il 02/10/20 alle ore 01:36:14