Uncertainty Measures in Interval-Valued Information Systems

摘要：

　　Rough set theory is a new mathematical tool to deal with vagueness and uncertainty in artificial intelligence.Approximation accuracy,knowledge granularity and entropy theory are three main approaches to uncertainty research in classical Pawlak information system,which have been widely applied in many practical issues.Based on uncertainty measures in Pawlak information systems,we propose rough degree,knowledge discernibility and rough entropy in interval-valued information systems,and investigate some important properties of them.Finally,the relationships between knowledge granulation,knowledge discerniblity and rough degree have been also discussed.

关键词： Upper and lower approximations rough sets uncertainty measures

作者: Nan Zhang Zehua Zhang

作者单位: School of Computer and Control Engineering, Yantai University,Yantai, Shandong, 264005, China College of Computer Science and Technology, Taiyuan University of Technology,Taiyuan, Shanxi, 030024

会议类型: 国际会议

会议名称: The 9th International Conference on Rough Sets and Knowledge Technology (RSKT 2014)(第九届粗糙集与知识技术国际会议)

会议地点: 上海

会议语种:英文

页码: 479-488

在线出版日期: 2014-10-24（万方平台首次上网日期，不代表论文的发表时间）