一类神经模糊学习算法的一些性质

2004 International Conference on Intelligent Mechatronics and Automation, 2004. Proceedings. Pub Date : 2004-08-26 DOI:10.1109/ICIMA.2004.1384212

Yan Shi, M. Mizumoto

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引用次数: 1

摘要

在本文中，我们试图分析两种;对近年来在模糊应用中广泛应用的传统神经模糊学习算法进行了模糊规则的整定，并对其性质进行了总结。这些性质表明，在实际的模糊应用中，使用传统的神经模糊学习算法有时很难或不方便构建最优模糊系统模型。

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Some properties on a class of neuro-fuzzy learning algorithms

In this paper, we try to analyze two kind; of conventional neuro-fuzzy learning algorithms, which are widely used in recent fuzzy applications for tuning fuzzy rules, and give a summarization of their properties. Some of these properties show that uses of the conventional neuro-fuzzy learning algorithms are sometimes dillicult or inconvenient for constructing an optimal fuzzy system model in practical fuzzy applications.

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2004 International Conference on Intelligent Mechatronics and Automation, 2004. Proceedings.

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