Novel reduction algorithm based on deciding expert knowledge

doi:10.3778/j.issn.1002-8331.2009.08.046

Computer Engineering and Applications ›› 2009, Vol. 45 ›› Issue (8): 149-152.DOI: 10.3778/j.issn.1002-8331.2009.08.046

• 数据库、信号与信息处理 • Previous Articles Next Articles

Novel reduction algorithm based on deciding expert knowledge

YUAN Jun-peng¹,SU Jie²,WANG Hong-sheng³

1.Institute of Scientific and Technical Information of China，Beijing 100038，China
2.School of Management Science and Engineering，Central University of Finance and Economics，Beijing 100081，China
3.Yantai Dongfang Electronics Information Industry Co.，Ltd，Yantai，Shandong 264000，China

Received:2008-01-23 Revised:2008-04-03 Online:2009-03-11 Published:2009-03-11
Contact: YUAN Jun-peng

新的专家主导的粗糙集属性约简算法

袁军鹏¹,宿洁²,王洪升³

1.中国科学技术信息研究所，北京 100038
2.中央财经大学管理科学与工程学院，北京 100081
3.烟台东方电子信息产业股份有限公司，山东烟台 264000

通讯作者: 袁军鹏

Abstract

Abstract: Reduction is an important concept introduced by rough sets theory，and seeking the Minimum Reduction（MR） is a NP-hard problem.This paper presents a novel reduction algorithm to search the optimal solution for MR.Based on a new 0-1 distinguish matrix and the mode of man-machine cooperation，a man-machine cooperative intelligent algorithm（Reduction Based on Deciding Expert Knowledge Algorithm，RBDEKA） is proposed for attribute reduction.Finally，the empirical analysis result on the Micro-Electromechanical Systems（MEMS） field shows that the RBDEKA is feasible and efficient.

Key words: rough sets, 0-1 distinguish matrix, reduction, man-machine cooperation

摘要： 最小约简问题是粗糙集理论中的一类NP-hard问题。在总结属性约简经典算法的基础上，采取“人机结合”的思想，将领域专家的智慧与基于0-1判别矩阵的模拟退火算法有效集成，提出基于专家主导的粗糙集属性约简算法，并在微机电系统领域对本文提出的算法进行了实证分析，结果表明该算法是有效的、可靠的。

关键词: 粗糙集, 0-1判别矩阵, 属性约简, 人机结合

YUAN Jun-peng¹,SU Jie²,WANG Hong-sheng³. Novel reduction algorithm based on deciding expert knowledge[J]. Computer Engineering and Applications, 2009, 45(8): 149-152.

袁军鹏¹,宿洁²,王洪升³. 新的专家主导的粗糙集属性约简算法[J]. 计算机工程与应用, 2009, 45(8): 149-152.

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Novel reduction algorithm based on deciding expert knowledge

新的专家主导的粗糙集属性约简算法

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