由于关系数据的竞争聚集算法能得到优化的固定的聚类个数，因此能挖掘出优化的模糊关联规则。
The optimal fuzzy association rules can be mined due to the optimal fixed clustering number that can be obtained by the relational competitive agglomeration algorithm.
讨论了区间值关系数据库上模糊关联规则的挖掘算法与预测方法。
Mining algorithm and prediction method of fuzzy association rules are discussed in this paper.
对数量型属性，应用竞争聚集算法将数量型属性划分成若干个模糊集，并系统地提出加权模糊关联规则的挖掘算法。
As for quantitative attributes, they are divided into several fuzzy sets by the competitive agglomeration algorithm, and then the algorithm for mining weighted fuzzy association rules is provided.
同时，设计出了FARM模糊动作关联规则算法，对企业关系价值真实数值型数据进行挖掘，并挖掘出提升企业关系价值的主要规则。
Meanwhile, FARM algorithm is designed to mine the real numerical data of enterprise relationship value. Then, the promotion rules of relationship value are put forward.
然后，在此基础上提出一种改进的模糊关联算法挖掘分类关联规则；
Secondly, an improved fuzzy association method was proposed to mine the classification association rules.
然后，在此基础上提出一种改进的模糊关联算法挖掘分类关联规则；
Secondly, an improved fuzzy association method was proposed to mine the classification association rules.
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