Knowledge Reducts to Incomplete Information System under the Similarity Relation
Certain rules and possible rules exist in incomplete information system, So membership function and generalized decision function under the similarity relation are proposed and some properties of them are proved. Based on the concepts,several types of knowledge redncts to object and system are defined under similarity relation, and mutual relationship among them is established. Several kinds of decision rules are defined according to the new definition of knowledge reducts. An example shows bow to generate optimal certain rule and optimal generalized rule by using discernibility function, and the result shows that different knowledge reducts lead to different decision rules. The research on types of knowledge reducts is the theory foundation of knowledge acquisition algorithms to incomplete information system.
rough theory incomplete information system similarity relation knowledge reducts
Li Ping Liu Xiao-juan Wu Xiao-lei Wu Qi-zong
School of Management and Economies Beijing Institute of Technology Beijing, China
国际会议
The 10th International Conference on Intelligent Technologies(第十届智慧科技国际会议 InTech09)
桂林
英文
601-607
2009-12-12(万方平台首次上网日期,不代表论文的发表时间)