...转换成知识的过程中，有许多 学者专家是以模糊规则(Fuzzy Rules)来表 示知识，以建构模糊分类系统(Fuzzy Classification Systems)。
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第一阶段，将模糊分类系统的前件和输入变量编码为一个个体，实现了输入变量论域的动态划分和输入变量选择。
In the first step, the antecedents of fuzzy classification system and input variables are coded into a binary string and treated as an individual in genetic algorithm.
新模糊分类系统具有以下优点：(1)可解释性好，(2)有效的特征压缩，(3)与传统方法相当的识别精度。
The new fuzzy classification system has some advantages as follows: (1) good interpretability, (2) efficient feature compression, (3) comparative accuracy to the traditional methods.
用这样一个模糊规则来表示分类的模糊系统，更加有效地构建了一个能对训练样本比较准确分类的模糊分类器。
This fuzzy system design method that uses a fuzzy rule to represent a cluster is then propsed so that a fuzzy classifier can be efficiently constructed to correctly classify the training data.
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