分类模糊关联规则挖掘模型及其在芳烃抽提中的应用

首先对现有的模糊关联规则挖掘算法中的支持度定义进行了改进，该支持度采用基于距离的定义方式.在此基础上，将决策树中目标属性的概念引入模糊关联规则挖掘中，提出了分类模糊关联规则挖掘模型;该模型在工业生产过程和现实生活中具有广泛的应用背景，而且较完全无指导的购物篮型关联规则挖掘问题更易于实现.最后，将这种分类模糊关联规则挖掘模型应用于芳烃抽提生产过程，通过对芳烃抽提生产过程的历史数据进行挖掘，找到了在芳烃生产过程中，当苯塔装置进料组分发生变化时，生产率降低、能耗增加的原因.

Classified fuzzy association rules mining model and its application in aromatic hydrocarbon extraction

The existing definition of support was improved by adopting a new definition based on distance.Then classified fuzzy association rules mining model (CFARMM) was proposed.It takes association rule mining techniques applicable to classification tasks by introducing the concept of the target variable of decision tree.CFARMM is not only widely applicable in industrial production process and real life, but also easily realized as compared with shopping baskets association rules mining problem.Finally, CFARMM was applied to mine the real aromatic hydrocarbon extraction process.Through the data mining of historical process, the reasons that recovery rate decreased, and energy loss increased when the feed components varied were found.