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Journal of Automation and Information Sciences
SJR: 0.232 SNIP: 0.464 CiteScore™: 0.27

ISSN Druckformat: 1064-2315
ISSN Online: 2163-9337

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Journal of Automation and Information Sciences

DOI: 10.1615/JAutomatInfScien.v45.i9.10
pages 1-12

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

Oleg G. Rudenko
Kharkov National University of Radio and Electronics, Kharkov
Alexander A. Bezsonov
Kharkov National University of Radio and Electronics, Kharkov

ABSTRAKT

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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