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基于数组的增量式属性约简研究*
引用本文:汪小燕,杨思春.基于数组的增量式属性约简研究*[J].计算机应用研究,2011,28(5):1728-1730.
作者姓名:汪小燕  杨思春
作者单位:安徽工业大学,计算机学院,安徽,马鞍山,243032
基金项目:安徽省教育厅自然科学项目(KJ2009B074Z);计算机软件新技术国家重点实验室开放课题基金资助项目(KFKT2010B02)
摘    要:为了在动态变化的决策表中,快速方便地获得新的属性约简,利用数组元素对差别矩阵中的属性组合进行计数,提出一种基于数组的增量式属性约简更新算法。当决策表动态变化时,根据数组元素的取值变化,获得差别矩阵中增加和减少的元素,依据这些元素更新原属性约简,快速得到新的最小属性约简。理论分析及实例验证了提出的算法是有效的。

关 键 词:粗糙集    属性约简    差别矩阵    增量式    数组
收稿时间:2010/11/3 0:00:00
修稿时间:2011/4/18 0:00:00

Research for incremental updating algorithm for attribute reduction based on array
WANG Xiao-yan,YANG Si-chun.Research for incremental updating algorithm for attribute reduction based on array[J].Application Research of Computers,2011,28(5):1728-1730.
Authors:WANG Xiao-yan  YANG Si-chun
Affiliation:WANG Xiao-yan,YANG Si-chun (School of Computer Science,Anhui University of Technology,Ma'anshan Anhui 243032,China)
Abstract:Using array elements to count attribute combination in discernibility matrix ,this paper introduced an incremental updating algorithm for attribute reduction based on array in order to obtain new attribute reduction quickly and conveniently in the dynamic decision table . When the decision table is in dynamic change , attribute combination increased and reduced can be obtained in discernibility matrix by the changes of the array element value. The old attribute reduction set can be updated effectively based on these attribute combination and the smallest attribute reduction set can be obtained quickly. The algorithm is proved to be efficient both by theoretical analysis and illustration of examples.
Keywords:rough set  attribute reduction  discernibility matrix  incremental  array
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