模糊神经网络模糊权值的调整

1998 Second International Conference. Knowledge-Based Intelligent Electronic Systems. Proceedings KES'98 (Cat. No.98EX111) Pub Date : 1998-04-21 DOI:10.1109/KES.1998.725940

T. Feuring, J. Buckley, Y. Hayashi

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引用次数: 7

摘要

为了训练模糊神经网络，必须调整模糊数的权重。由于模糊算法会自动导致输出单调递增，因此直接模糊化反向传播方法是行不通的。因此，重点是其他策略，如进化算法。本文提出了一种基于反向传播的权重调整方法。进一步证明了该方法的收敛性是有保证的。

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Adjusting fuzzy weights in fuzzy neural nets

In order to train fuzzy neural nets fuzzy number weights have to be adjusted. Because fuzzy arithmetic automatically leads to monotonic increasing outputs a direct fuzzification of the backpropagation method does not work. Therefore, the focus is on other strategies like evolutionary algorithms. In this paper we suggest a backpropagation based method of adjusting the weights. Furthermore we can show that for the proposed method convergence can be guaranteed.

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1998 Second International Conference. Knowledge-Based Intelligent Electronic Systems. Proceedings KES'98 (Cat. No.98EX111)

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