摘要
针对道路运输管理信息数据大多不一致、不精确和不完整的特点,基于粗糙集理论中的系统归纳思想和属性约简方法,提出了粗糙集分析与经典关联规则相结合的数据挖掘方法,并利用粗糙集方法分析了规则条数与支持度、置信度之间的关系;最后通过道路运输管理的实际案例对该方法的科学性、有效性进行了验证.结果表明,该方法对于解决道路运输管理的实际问题切实可行,对于选用的实际案例可实现约简33.3%条件属性的优化效果.
As the data of the road transportation management information system are mostly inconsistent,imprecise and incomplete,a novel data mining method,which combines the rough set analysis with the classical association rule,is proposed based on the system induction idea and the attribute reduction method of the rough set theory. Then,the relationship among the rule number,the support degree and the confidence is analyzed by using the rough set method,and the reliability and validity of the proposed method is verified through a case study.The re-sults indicate that the proposed method can realize an attribute reduction of 33 .3%,which means that the method is effective in solving the problems existing in the real road transportation management system.
出处
《华南理工大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2014年第2期132-138,共7页
Journal of South China University of Technology(Natural Science Edition)
基金
国家自然科学基金资助项目(61174184)
广州市科技支撑计划项目(2011J4300045)
关键词
道路运输
管理信息
粗糙集
关联规则
数据挖掘
road transportation
management information
rough set
association rule
data mining
