A destructive learning method of fuzzy inference rules
A destructive learning method of fuzzy inference rules
复制标题
一种模糊推理规则破坏性学习方法
DOI：
10.1109/fuzzy.1995.409758
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发表时间：
1995
期刊：
影响因子：
--
通讯作者：
Y. Nagasawa
中科院分区：
文献类型：
--
作者：
S. Fukumoto;H. Miyajima;K. Kishida;Y. Nagasawa
为了构造一个具有学习功能的模糊系统，许多研究将模糊系统与神经网络（或下降法）相结合。Ichihashi等人（1991）提出了使用下降法的自校正方法，并且已知构造性方法比使用神经网络（或下降法）的其他方法更强大。但这种方法对所获得的知识不具有足够的泛化能力和表达能力。在本文中，我们提出了一种新的学习方法称为下降法的模糊推理规则的破坏性方法。我们发现，破坏性的方法是上级的规则和推理错误的数量，但在学习速度不如建设性的。此外，为了提高学习速度，我们提出了一种结合建设性和破坏性的学习方法。数值算例表明了所提方法的有效性，并给出了这些方法在避障问题中的应用。<<ETX>>
In order to construct a fuzzy system with a learning function, numerous studies combining fuzzy systems and neural networks (or descent method) are being carried out. The self-tuning method using the descent method has been proposed by Ichihashi et al. (1991) and it is known that the constructive method is more powerful than other methods using neural networks (or descent method). But this method does not have a sufficient generalization capability or an expressing capability for the acquired knowledge. In this paper, we propose a new learning method called a destructive method of fuzzy inference rules by the descent method. And we show that the destructive method is superior in the number of rules and inference errors but inferior in learning speed to the constructive one. Further more, in order to improve learning speed, we propose a learning method combining the constructive and the destructive methods. Some numerical examples are given to show the validity of the proposed methods, and applications of these methods to the obstacle avoidance problem are shown.<<ETX>>