Abstract：A covering reduction algorithm is studied under the condition that both the upper approximation operator and the under approximation operator are not changed. The absolute information quantity, information quantity and the adjacency matrix are defined. An incremental reduction algorithm is presented based on the absolute information quantity for covering generalized rough sets. The example shows that the proposed algorithm is an effective technique to remove the redundant knowledge in the complex datasets.
林国平，李进金. 基于绝对信息量的覆盖增量约简算法[J]. 模式识别与人工智能, 2011, 24(2): 210-214.
LIN Guo-Ping, LI Jin-Jin. A Covering Incremental Reduction Algorithm Based on Absolute Information Quantity. , 2011, 24(2): 210-214.
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2011, Vol. 24 
