摘要
全粒度粗糙集是一种动静结合的粗糙集模型,在一定程度上可以表示人类认识的复杂性、多样性和不确定性.文中定义概念的全粒度属性约简,完善全粒度粗糙集属性约简的定义.探索概念的全粒度属性约简、全粒度绝对约简及全粒度Pawlak约简的性质,指明这些属性约简之间的关系,有助于全粒度属性约简的实际应用及启发式算法的产生.
Entire-granulation rough sets is a kind of dynamic and static combining rough set model. They can partly express complexity, diversity and uncertainty of human cognition. The entire-granulation attribute reducts for a single concept are defined and the definitions of attribute reducts for entire- granulation rough sets are completed. The properties of entire-granulation attribute reducts, including entire-granulation attribute reducts for a single concept, entire-granulation absolute attribute reducts and entire-granulation Pawlak reducts, are investigated. Moreover, the relationships among various kinds of entire-granulation attribute reduets are studied. The obtained results contribute to practical applications and the generation of heuristic algorithms of entire-granulation attribute reducts.
作者
邓大勇
DENG Dayong1(1. Xingzhi College, Zhejiang Normal University, Jinhua 32100)
出处
《模式识别与人工智能》
EI
CSCD
北大核心
2018年第3期230-235,共6页
Pattern Recognition and Artificial Intelligence
基金
浙江省自然科学基金项目(No.LY15F020012)资助~~
关键词
全粒度粗糙集
概念的全粒度属性约简
全粒度绝对约简
全粒度Pawlak约简
属性约简
Entire-Granulation Rough Sets, Entire-Granulation Attribute Reducts for a SingleConcept, Entire-Granulation Absolute Reducts, Entire-Granulation Pawlak Reducts,Attribute Reducts
