期刊
APPLIED SOFT COMPUTING
卷 24, 期 -, 页码 423-431出版社
ELSEVIER
DOI: 10.1016/j.asoc.2014.07.023
关键词
Neural network control; Nonlinear systems; Gradient descent method; Supervised and unsupervised learning; Self-organizing map; Hybrid learning
In this paper, a hybrid method is proposed to control a nonlinear dynamic system using feedforward neural network. This learning procedure uses different learning algorithm separately. The weights connecting the input and hidden layers are firstly adjusted by a self organized learning procedure, whereas the weights between hidden and output layers are trained by supervised learning algorithm, such as a gradient descent method. A comparison with backpropagation (BP) shows that the new algorithm can considerably reduce network training time. (C) 2014 Elsevier B.V. All rights reserved.
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