基于模糊等价关系的粗糙集方法

Rough Set Methods Based on Fuzzy Equivalence Relationship

在对研究信息系统中知识不完全、不确定问题的两种重要理论粗糙集和模糊集进行比较分析的基础上,结合模糊集和粗糙集各自的优点,针对信息系统中数据量庞大且属性值大多是连续的、很多数据对象具有相同或相似性质的情况,提出一种基于模糊等价关系的粗糙集方法,实现了粗糙集理论与模糊集理论的有机结合;并通过一个应用实例,证明了此方法的有效性.

First of all, the two major theories of rough sets and fuzzy sets which study partial and uncertain knowledge in information systems are compared and analyzed; combining their own merits of fuzzy sets and rough sets, aiming at the huge data and continuous attributes in information system, and a lot of data objects with the same or similar nature, the method of rough set is proposed based on fuzzy equivalence relationship, achieving organic combination of rough set theory and fuzzy set theory. Finally, an application example was illustrated and proves that the approach is effective.