A simple and quick algorithm, integrated with weighted distribution and Hamming distance, is derived from the principle of fuzzy similarity-ratio.

从模糊相似比原理出发，推证出一种简捷的快速算法，并综合了权重和海明距离两方面因素，从而使模糊相似比方法得到改进。

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Based on fuzzy C-Means algorithm (FCM) and fuzzy Min-Max Neural Networks, an integrated algorithm for fuzzy pattern recognition using hypercube set was proposed.

结合模糊c均值算法(FCM)与模糊最小最大神经网络算法，提出一种基于超长方体集的模糊模式识别算法。

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The neural network-based adaptive control and fuzzy logic are integrated based on feedback learning algorithm.

在反馈学习算法的基础上，将模糊逻辑和神经网络自适应控制的结构结合在一起。

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