RBF CENTERS INITIALIZATION USING FUZZY CLUSTERING TECHNIQUE FOR FUNCTION APPROXIMATION PROBLEMS

In this paper, a new algorithm for RBF centers initialization for functional approximation problems is proposed. The design of the algorithm is inspired in previous clustering algorithms but adding some features to adapt the algorithm to the characteristics of our problem. We compare the results provided by our new algorithm with the results provided by the algorithms it is based on.

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Year of publication:	2005
Authors:	Guillén, A. ; Rojas, I. ; González, J. ; Pomares, H. ; Herrera, L.J.
Published in:	Fuzzy Economic Review. - International Association for Fuzzy-Set Management and Economy - SIGEF, ISSN 1136-0593. - Vol. X.2005, 2, p. 27-44
Publisher:	International Association for Fuzzy-Set Management and Economy - SIGEF
Subject:	Neural networks \| radial basis functions \| function approximation \| clustering

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Type of publication:	Article
Classification:	G17 - Financial Forecasting
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10004992718