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Neural Computing and Applications

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01.10.2009 | Original Article

A hybrid MPSO-BP structure adaptive algorithm for RBFNs

verfasst von: Shiwei Yu, Kejun Zhu, Siwei Gao

Erschienen in: Neural Computing and Applications | Ausgabe 7/2009

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Abstract

This paper introduces a novel hybrid algorithm to determine the parameters of radial basis function neural networks (number of neurons, centers, width and weights) automatically. The hybrid algorithm combines the mix encoding particle swarm optimization algorithm with the back propagation (BP) algorithm to form a hybrid learning algorithm (MPSO-BP) for training Radial Basis Function Networks (RBFNs), which adapts to the network structure and updates its weights by choosing a special fitness function. The proposed method is used to deal with three nonlinear problems, and the results obtained are compared with existent bibliography, showing an improvement over the published methods.

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Titel: A hybrid MPSO-BP structure adaptive algorithm for RBFNs
verfasst von: Shiwei Yu
Kejun Zhu
Siwei Gao
Publikationsdatum: 01.10.2009
Verlag: Springer-Verlag
Erschienen in: Neural Computing and Applications / Ausgabe 7/2009
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI: https://doi.org/10.1007/s00521-008-0214-2

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