多粒度粗糙集的双层绝对约简

Double-Level Absolute Reduction for Multi-granulation Rough Sets

多粒度粗糙集本质上是异构的,但是目前尚未运用于异构数据处理.从绝对约简的角度出发,提出多粒度粗糙集的双层绝对约简——多粒度绝对约简和多粒度绝对粒度约简.分析多粒度双层绝对约简的性质,特别是从异构数据约简的角度探究多粒度双层绝对约简的特性,提出多粒度双层绝对约简算法.理论分析和实例表明多粒度双层绝对约简算法的可行性.

Multi-granulation rough set is a rough set model for heterogenous data in essence. However, it is still not employed to deal with heterogenous data. From the viewpoints of absolute attribute reduction, double-level absolute reduction for multi-granulation rough sets is proposed, including multi-granulation absolute recducts and multi-granulation absolute granulation reducts, and properties of double-level absolute reduction are analyzed from the perspective of heterogenous data. The algorithms for double-level absolute reduction are presented. Theoretical analysis and example show the validation of multi-granulation absolute reducts, multi-granulation absolute granulation reducts and double-level absolute reducts.