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Abstract:
In order to adjust the structure and parameter of a fuzzy neural network simultaneously, a growing fuzzy neural network based on the unscented Kalman filter(UKF) method is proposed. Firstly, the UKF method is used to adjust the parameters of the fuzzy neural network. Then, a growing mechanism, using the output intensity of hidden neurons, is designed for self-organizing the fuzzy rules, and the structure of fuzzy neural networks can grow in the learning process. Finally, the proposed growing fuzzy neural network is used to model a nonlinear system. The experimental results show that the proposed growing fuzzy neural network is able to adjust the structure and parameters simultaneously, as well as with suitable modeling accuracy. © 2017, Editorial Office of Control and Decision. All right reserved.
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Control and Decision
ISSN: 1001-0920
Year: 2017
Issue: 12
Volume: 32
Page: 2169-2175
Cited Count:
SCOPUS Cited Count: 2
ESI Highly Cited Papers on the List: 0 Unfold All
WanFang Cited Count:
Chinese Cited Count:
30 Days PV: 10
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