摘要
通过在决策序信息系统中引入证据理论,提出一种基于粗糙集的证据获取与合成方法。利用证据信任度计算近似条件概率分配,根据属性重要度和证据支持度计算权重,然后用合成公式对近似条件概率分配进行合成,得到决策。
A novel method of evidence acquirement and combination based on rough set was proposed by introducing evi- dence theory into the ordered decision information system. Confidence degrees of evidence are used to calculate approxi- mate conditional probability assignments. Evidence weights are calculated according to the attribute significances and support degrees of evidence. Decisions are gained by using combinational rule to integrate approximate conditional probability assignments.
出处
《计算机科学》
CSCD
北大核心
2015年第6期54-56,共3页
Computer Science
基金
国家自然科学基金(61105041,61472463,61402064)
重庆市自然科学基金资助项目(cstc2013jcyjA40051)
南京理工大学高维信息智能感知与系统教育部重点实验室基金(30920140122006)资助
关键词
粗糙集
近似条件概率分配
序信息系统
证据理论
证据支持度
Rough set
Approximate conditional probability assignment
Ordered information system
Evidence theory
Support degrees of evidence
