摘要
目前区间值信息系统的不确定性度量方法大多基于粗糙集的粗糙度度量。实例分析表明该度量方法不满足严格单调性,为了解决这一缺陷,将粒计算方法引入区间值信息系统中,提出一种区间值信息系统的信息粒化模型。引入区间值信息系统的知识粒度和粗糙熵两种度量方法,理论分析出它们具有的严格单调性,在区间值信息系统的不确定性度量方面具有更好的优越性。实验验证了知识粒度和粗糙熵均比传统的粗糙度具有更好的不确定性度量效果。
At present,the uncertainty measurement methods of interval-valued information system are mostly based on the roughness measurement of rough set.An example is given to show that the measurement method does not satisfy the strict monotonicity.In order to solve this problem,the granular computing method is introduced into the interval-valued information system,and the granular model of the interval-valued information system is proposed.The knowledge granularity and rough entropy of the interval-valued information system were introduced.Theoretical analysis shows that these two methods are strictly monotonic and have better advantages in uncertainty measurement of interval-valued information system.Finally,the experimental verification and analysis show that knowledge granularity and rough entropy have better uncertainty measurement effect than traditional roughness.
作者
甘秀娜
李明
王月波
Gan Xiuna;Li Ming;Wang Yuebo(Organization and Personal Department,Shijiazhuang Institute of Railway Technology,Shijiazhuang 050041,Hebei,China;Department of Economic Management,Shijiazhuang Tiedao University Sifang College,Shijiazhuang 051132,Hebei,China;Information Technology Department,Bank of Hebei Co.,Ltd.,Shijiazhuang 050000,Hebei,China)
出处
《计算机应用与软件》
北大核心
2021年第8期107-114,共8页
Computer Applications and Software
基金
河北省社会科学基金项目(HB14GL023)
河北省高等学校科学技术研究项目(QN2014035)
河北省科技计划项目(13456119D)。
关键词
区间值信息系统
不确定性度量
粗糙集
粒计算
知识粒度
粗糙熵
Interval-valued information system
Uncertainty measurement
Rough set
Granular computing
Knowledge granularity
Rough entropy
