Matrix-based approaches for dynamic updating approximations in multigranulation rough sets
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摘要
Multigranulation rough set, which is constructed by a family of equivalence relations has attracted much attention, because it offers a theoretical framework for the problem solving in the view of multigranulation. However, the granular structure in the information systems often dynamically evolves over time. How to dynamically obtain the potential useful knowledge for decision making is of great significance in the context of multigranulation. Motivated by this requirement, in this paper, we present the definitions of equivalence relation matrix, diagonal matrix and cut matrix for a single granular structure in multigranulation rough set, and propose a matrix representation of multigranulation approximations in optimistic and pessimistic multigranulation rough set. Then, corresponding matrix-based dynamic approaches for updating approximations are proposed in multigranulation rough set when a single granular structure evolves over time. The experimental evaluations show the effectiveness of the proposed matrix-based dynamic updating algorithms compared with the matrix-based static algorithm.
论文关键词:Knowledge discovery,Updating approximations,Multigranulation,Matrix
论文评审过程:Received 6 October 2016, Revised 21 December 2016, Accepted 21 January 2017, Available online 23 January 2017, Version of Record 27 February 2017.
论文官网地址:https://doi.org/10.1016/j.knosys.2017.01.030