Computer Science ›› 2017, Vol. 44 ›› Issue (9): 78-82, 104.doi: 10.11896/j.issn.1002-137X.2017.09.016

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Distribution Reduction in Inconsistent Interval-valued Decision Systems

ZHANG Nan, XU Xin, TONG Xiang-rong, GAO Xue-yi and JIANG Li-li   

  • Online:2018-11-13 Published:2018-11-13

Abstract: Different classification features in decision systems can be kept by knowledge reduction which is one of the hottest issues in rough set theory.The confidence level is unchanged because of distribution reduction in decision systems.For providing the measure criterion for universe classification in interval-valued decision systems,the similarity coefficient was introduced in this paper.To extend the equivalence relation in Pawlak decision systems to the tolerance relation in interval-valued decision systems,we proposed the concept of distribution reduction in inconsistent interval-valued decision systems.Aiming at the proposed concept,we provided the computational method of corresponding discernibility matrix.We also discussed the relation of distribution reduction and generalized decision reduction in interval-valued decision systems.Finally,experiments show that the novel method is effective.

Key words: Knowledge reduction,Interval-valued decision systems,Distribution reduction,Tolerance relation

[1] MIAO D Q,ZHAO Y,YAO Y Y,et al.Relative reducts in consistent and inconsistent decision tables of the Pawlak rough set model[J].Information Sciences,2009,179(24):4140-4150.
[2] CHEN Z C.The study of knowledge discovery and attributes reduction in set-valued informations systems[D].Chengdu:Southwest Jiaotong University,2011.(in Chinese) 陈子春.集值信息系统的知识发现与属性约简研究[D].成都:西南交通大学,2011.
[3] ZHANG N,MIAO D Q,YUE X D.Approaches to Knowledge Reduction in Interval-Valued Information Systems[J].Journal of Computer Research and Development,2010,47(8):1362-1371.(in Chinese) 张楠,苗夺谦,岳晓冬.区间值信息系统的知识约简[J].计算机研究与发展,2010,47(8):1362-1371.
[4] DENG D Y,HUANG H K,LI X J.Comparison of various types of reductions in inconsistent systems[J].Chinese Journal of Electronics,2007,35(2):252-255.(in Chinese) 邓大勇,黄厚宽,李向军.不一致决策系统中约简之间的比较[J].电子学报,2007,35(2):252-255.
[5] XU F F,LEI J S,BI Z Q,et al.Approaches to approximate reduction with interval-valued multi-decision tables in big data[J].Journal of Software,2014,25(9):2119-2135.(in Chinese) 徐菲菲,雷景生,毕忠勤,等.大数据环境下多决策表的区间值全局近似约简[J].软件学报,2014,25(9):2119-2135.
[6] PAWLAK Z.Rough sets [J].International Journal of Computer &Information Sciences,1982,11(5):341-356.
[7] WANG G Y,YAO Y Y,YU H.A survey on rough set theory and applications[J].Chinese Journal of Computers,2009,32(7):1229-1246.(in Chinese) 王国胤,姚一豫,于洪.粗糙集理论与应用研究综述[J].计算机学报,2009,32(7):1229-1246.
[8] MIAO D Q,HU G R.A heuristic algorithm for reduction of knowledge[J].Journal of Computer Research and Development,1999,36(6):681-684.(in Chinese) 苗夺谦,胡桂荣.知识约简的一种启发式算法[J].计算机研究与发展,1999,36(6):681-684.
[9] ZHANG W X,MI J S,WU W Z.Knowledge reductions in inconsistent information systems[J].Chinese Journal of Computers,2003,26(1):12-18.(in Chinese) 张文修,米据生,吴伟志.不协调目标信息系统的知识约简[J].计算机学报,2003,26(1):12-18.
[10] DOMINIK S.The rough Bayesian model for distributed decision systems[C]∥Proceedings of 4th International Conference on Rough Sets and Current Trends in Computing.2004:384-393.
[11] XU W H,ZHANG W X.Distribution reductions in inconsistent information systems based on dominance relations[J].Fuzzy Systems and Mathematics,2007,21(4):124-131.(in Chinese) 徐伟华,张文修.基于优势关系下不协调目标信息系统的分布约简[J].模糊系统与数学,2007,21(4):124-131.
[12] 徐伟华.序信息系统与粗糙集[M].北京:科学出版社,2013:27-46.
[13] DU W S,HU B Q.Approximate distribution reducts in inconsistent interval-valued ordered decision tables[J].Information Sciences,2014,271(7):93-114.
[14] ZHANG X,MEI C L,CHEN D G,et al.Multi-confidence rule acquisition and confidence-preserved attribute reduction in interval-valued decision systems[J].International Journal of Approxi-mate Reasoning,2014,55(8):1787-1804.
[15] ZHOU J.Research on Knowledge Acquisition Algorithms inProbabilistic Rough Set Models[D].Shanghai:Tongji University,2011.(in Chinese) 周杰.概率粗糙集模型的知识获取算法研究[D].上海:同济大学,2011.
[16] QIN K Y,PEI Z,DU W F.The relationship among several know-ledge reduction approaches[C]∥Proceedings of the Second International on Fuzzy Systems and Knowledge Discovery.2005:1232-1241.

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