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Journal of Automation and Information Sciences

Publicado 12 números por año

ISSN Imprimir: 1064-2315

ISSN En Línea: 2163-9337

SJR: 0.173 SNIP: 0.588 CiteScore™:: 2

Indexed in

Robust Multiobjective Identification of Nonlinear Objects Based on Evolving Radial Basis Networks

Volumen 45, Edición 9, 2013, pp. 1-12
DOI: 10.1615/JAutomatInfScien.v45.i9.10
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SINOPSIS

The problem of multiobjective neural network-based identification of nonlinear objects by evolving radial basis network is considered. Networks structure selection and adaptation is performed using a genetic algorithm. Robust fitness functions are used to eliminate non-Gaussian noise. Robust information criteria are utilized for selection of the optimal model from the Pareto front. The simulation results confirm the effectiveness of the proposed approach.

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