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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
computer science
Automatic selection for the beta basis function neural networks
Studies in Computational Intelligence, Volume 129, Year 2008
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Description
In this paper, we propose a differential evolution algorithm based design for the beta basis function neural network. The differential Evolution algorithm has been used in many practical cases and has demonstrated good convergences properties. The differential evolution is used to evolve the beta basis function neural networks topology. Compared with the traditional genetic algorithm, the combined approach proves goodly the difference, including the feasibility and the simplicity of implementation. In the prediction of Mackey-Glass chaotic time series, the networks designed by the proposed approach prove to be competitive, or even superior, to the traditional learning algorithm for a multi-layer Perceptron network and radialbasis function network. Therefore, designing a set of BBFNN can be considered as solution of a two-optimisation problem. © 2008 Springer-Verlag Berlin Heidelberg.
Authors & Co-Authors
Dhahri, Habib
Tunisia
Research Group on Intelligent Machines
Alimi, Adel M.
Tunisia
Research Group on Intelligent Machines
Statistics
Citations: 9
Authors: 2
Affiliations: 1
Identifiers
Doi:
10.1007/978-3-540-78987-1_42
ISSN:
1860949X
Research Areas
Genetics And Genomics