一种飞行数据的模糊关联规则挖掘算法*

提出利用模糊属性集和关联规则的支持度获得高效率的关联规则增量更新挖掘的方法。首先对输入数据集进行模糊离散化，确定相应的模糊属性集，模糊支持数和各属性原先的模糊聚类中心；然后检查是否满足最小支持度条件，将其添加到更新后的模糊频繁属性集集合中；最后比较模糊频繁属性集和负边界的变化，得到最终更新后的模糊频繁属性集和相应的关联规则。采用实际飞行数据验证了该算法可以避免反复和多层扫描数据库的时间消耗问题，模糊关联规则挖掘算法可以高效和准确提取增量关联规则。

Study of incremental updating fuzzy association mining rules based on flight data

This paper used the fuzzy attribute dataset and support of association rule to get more efficient incremental updating association mining rules.Firstly, the input dataset,determined the fuzzy supporting and the center of fuzzy clustering after fuzzy-discreting. Secondly, added the minimum support to the fuzzy attribute dataset when it met the min-support. At last, compared the change of fuzzy frequent attribute and negative boundary to get the dataset and rule. The method avoids time consuming in scanning multilayer repeatly and in dataset.In coclusion, this method can mining the incremental association rules efficiently and correctly.