自动化与信息科学期刊
每年出版 12 期
ISSN 打印: 1064-2315
ISSN 在线: 2163-9337
SJR:
0.173
SNIP:
0.588
CiteScore™::
2
Indexed in
Robust Multiobjective Identification of Nonlinear Objects Based on Evolving Radial Basis Networks
卷 45,
册 9, 2013,
pp. 1-12
DOI: 10.1615/JAutomatInfScien.v45.i9.10
摘要
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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