当前位置: X-MOL 学术Soft Comput. › 论文详情
Generic extended multigranular sets for mixed and incomplete information systems
Soft Computing ( IF 2.784 ) Pub Date : 2020-02-10 , DOI: 10.1007/s00500-020-04748-4
Yenny Villuendas-Rey, Cornelio Yáñez-Márquez, José Luis Velázquez-Rodríguez

Abstract Granular computing is a widely used computational paradigm nowadays. Particularly, within the rough set theory, granular computing plays a key role. In this paper, we propose a generic approach of rough sets, the granular extended multigranular sets (GEMS) for dealing with both mixed and incomplete information systems. Not only our proposal does use the traditional optimistic and pessimistic granulations with respect to single attributes, but also we introduce granulations with respect to attribute sets, as well as two new ways of granulating: the optimistic + pessimistic granulation and the pessimistic + optimistic granulation. In addition, we have developed a particular case of the proposed GEMS: the multigranular maximum similarity rough sets (MMSRS). We have proved some of the properties of the MMSRS, and we tested its effectiveness with respect to other existing granular rough sets models. The experimental results show the flexibility and the capabilities of the proposed model, while handling mixed and incomplete information systems.
更新日期:2020-03-24

 

全部期刊列表>>
宅家赢大奖
向世界展示您的会议墙报和演示文稿
全球疫情及响应:BMC Medicine专题征稿
新版X-MOL期刊搜索和高级搜索功能介绍
化学材料学全球高引用
ACS材料视界
x-mol收录
自然科研论文编辑服务
南方科技大学
南方科技大学
舒伟
中国科学院长春应化所于聪-4-8
复旦大学
课题组网站
X-MOL
香港大学化学系刘俊治
中山大学化学工程与技术学院
试剂库存
天合科研
down
wechat
bug