摘要
根据不完备信息系统(IIS)的数据不完整或不完备的特性,从粗糙集(RS)等价类的概念出发,提出了基于粗糙集理论的不完整数据集知识获取方法,利用该算法不仅可以从不完整数据集中提取规则,并且能够解决在学习过程中对训练事例属性未知特征值的估计问题。最后,给出具体的算例利用所给的算法求得信息系统的知识获取,并对所得的结果进行比较,从而说明所给算法的有效性和实用性,也证实了该算法可以有效地应用于复杂工业过程的专家系统知识库的建立。
To the property of incomplete pending data in the incomplete information system（IIS）,a kind of knowledge acquiring method for IIS is presented based on the rough set theory and the equivalence class concept.Using the algorithm,not only some certain or possible rules can be easily extracted from the incomplete data,but also the unknown attribute eigenvalue estimattion problem can be resolved.The validity and practicability of the algorithm is proven,and the acquired knowledge of the information system is shown through a practical example.The algorithm is also validity in the construction of the expert system knowledge base.
出处
《控制工程》
CSCD
北大核心
2010年第6期782-784,788,共4页
Control Engineering of China
基金
湖南省自然科学基金资助项目(09JJ3129)
湖南省科技计划基金资助项目(2009GK2002)
关键词
不完备信息
粗糙集
粗糙集等价类
知识获取
incomplete information
rough set
equivalence class of rough set
knowledge acquiring
