BeeRBF: A bee-inspired data clustering approach to design RBF neural network classifiers-Reference-Cited by-同舟云学术

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BeeRBF: A bee-inspired data clustering approach to design RBF neural network classifiers

Published:2016-01 Issue: Volume:172 Page:427-437
ISSN:0925-2312
Container-title:Neurocomputing
language:en
Short-container-title:Neurocomputing

Author:

Ferreira Cruz Dávila Patrícia,Dourado Maia Renato,da Silva Leandro Augusto,de Castro Leandro Nunes

Funder

Capes

Fapesp

CNPq

MackPesquisa

Fapemig

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference44 articles.

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2. A sequential learning scheme for function approximation using minimal radial basis function neural networks;Yingwei;Neural Comput.,1997

3. An efficient method to construct radial basis function neural network classifier;Hwang;Neural Netw.,1997

4. Cooperative-competitive genetic evolution of radial basis function centers and widths for time series prediction;Whitehead;IEEE Trans. Neural Netw.,1996

5. L. De Castro, E. Hruschka and R. J. G. B. Campello, An evolutionary clustering technique with local search to design RBF neural network classifiers, in: Proceedings of the IEEE International Joint Conference on Neural Network, 2004.

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