Computer Science ›› 2018, Vol. 45 ›› Issue (7): 178-185.doi: 10.11896/j.issn.1002-137X.2018.07.031

• Artificial Intelligence • Previous Articles     Next Articles

Local Attribute Reduction in Interval-valued Decision Systems

YIN Ji-liang ,ZHANG Nan ,ZHAO Li-wei ,CHEN Man-ru   

  1. Key Lab for Data Science and Intelligence Technology of Shandong Higher Education Institutes, Yantai University,Yantai,Shandong 264005,China;
    School of Computer and Control Engineering,Yantai University,Yantai,Shandong 264005,China
  • Received:2018-03-17 Online:2018-07-30 Published:2018-07-30

Abstract: The existing attribute reduction in interval-valued decision system is mainly relative to all decision classes.For some special classes of decision attributes in interval-valued decision system,the concept of local reduction and the judgment theorem of partial decision classes were introduced in this paper.Besides,the structure of local reduction was studied by using the method of discernibility matrix,and the local reduction algorithm based on discernibility matrix was given.The structure of the global reduction in interval-valued decision system was further depicted through the concept of the local reduction,and the relationship between the local reduction and global reduction was discussed.Finally,related experiments were carried out.The experimental results show the feasibility and effectiveness of the proposed algorithm.

Key words: Discernibility matrix, Global reduction, Interval-valued decision system, Local reduction, Specific classes

CLC Number: 

  • TP181
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