Rough Set Method Based on Multi-Granulations

摘要：

The original rough set model is concerned primarily with the approximation of sets described by single binary relation on universe. In the view of granular computing, classical rough set theory is researched by single granulation (static granulation). The article extends the Pawlak rough set model to rough set model based on multi-granulations MGRS, where the set approximations are defined by using multi-equivalences on the universe. Mathematical properties of MGRS are investigated. It is shown that some properties of Pawlak rough set are special instances of MGRS, approximation measure of set described by using multi-granulations is always better than by using single granulation, which is suitable for describing more accurately the concept and solving problem according to user requirement.

关键词： Rough set Multi-granulations Approximation measure.

作者: Y.H.Qian J.Y.Liang

作者单位: Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education School of Computer and Information Technology, Shartxi University Taiyuan, 030006, Peoples Republic of China

会议类型: 国际会议

会议名称: Firth IEEE International Conference on Cognitive Informatics(第五届认知信息国际会议)

会议地点: 北京

会议语种:英文

页码: 297-304

在线出版日期: 2006-07-17（万方平台首次上网日期，不代表论文的发表时间）