ROUGH PROBABILITY AND ROUGH EXPECTED VALUE MODELS

摘要：

Rough set theory is a new and effective mathematical theory used for processing incomplete, uncertain and vague data. In this paper, new set-theoretic operators — rough operators are proposed based on Pawlak rough set. On the basis of rough operators, a self-duality measure — rough probability is presented. On the rough probability space, rough variable, rough distribution, and rough expected value are introduced, their some properties are given. Finally, rough expected value models are established, and the rough expected value model of the convexity theorem is proved.

关键词： Rough probability Rough variable Rough ezpected value Rough ezpected value models

作者: YI-JUN FAN DA-ZENG TIAN MING-HU HA

作者单位: College of Mathematics & Computer Science, Hebei University, Baoding 071002, China College of Physics Science and Technology, Hebei University, Baoding 071002, China

会议类型: 国际会议

会议名称: 2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)

会议地点: 昆明

会议语种:英文

页码: 2357-2362

在线出版日期: 2008-07-12（万方平台首次上网日期，不代表论文的发表时间）