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Journal of Automation and Information Sciences
SJR: 0.275 SNIP: 0.59 CiteScore™: 0.8

ISSN 印刷: 1064-2315
ISSN オンライン: 2163-9337

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Journal of Automation and Information Sciences

DOI: 10.1615/JAutomatInfScien.v46.i11.20
pages 9-22

Multiobjective Optimization of Evolving Feedforward Neural Networks

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

要約

The paper has proposed to utilize a multicriteria approach to training evolutionary feedforward neural networks. The general structure of such neural networks is considered. A comparative analysis of single-objective, scalarized multiobjective learning and Pareto-based multiobjective learning is performed. Simulation in the presence of noisy measurements with different distribution laws has confirmed the effectiveness of the suggested approach.


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