Computer Science ›› 2016, Vol. 43 ›› Issue (6): 204-207.doi: 10.11896/j.issn.1002-137X.2016.06.041

Previous Articles     Next Articles

Approach to Knowledge Reduction Based on Inconsistent Confidential Dominance Principle Relation

GOU Guang-lei and WANG Guo-yin   

  • Online:2018-12-01 Published:2018-12-01

Abstract: Confidential dominance relation based rough set model is used to deal with incomplete ordered decision system,in which knowledge reduction is one of the most important problems.In order to discern two objects in IODS,their decision preference should be taken into account.This paper proposed a knowledge reduction approach based on inconsistent confidential dominance principle relation,with which two objects are discernable.Furthermore,the judgment theo-rems and the discernable matrix are investigated,from which we can obtain a new approach to knowledge reduction in ordered decision system.An example illuminates effectiveness of the new reduction.

Key words: IODS,Knowledge reduction,Confidential dominance relation,Inconsistent confidential dominance principle relation

[1] Dembczyński K,Greco S,Kotowski W,et al.Quality of rough approximation in multi-criteria classification problems[M]∥Rough Sets and Current Trends in Computing.Springer Berlin Heidelberg,2006:318-327
[2] Greco S,Matarazzo B,Slowinski R.Rough Approximation by Dominance Relations[J].International Journal of Intelligent Systems,2002,17(2):153-171
[3] Pawlak Z,Skowron A.Rudiments of rough sets[J].Information Sciences,2007,177(1):3-27
[4] Gou Guang-lei,Wang Guo-yin,Li Jie,et al.Confidential dominance relation based rough approximation model[J].Control and Decision,2014,9(7):1325-1329(in Chinese) 苟光磊,王国胤,利节,等.基于置信优势关系的粗糙集近似模型[J].控制与决策,2014,9(7):1325-1329
[5] Susmaga R,Slowinski R.Generation of rough sets reducts and constructs based on inter-class and intra-class information[J].Fuzzy Sets and Systems,2015,4(1):124-142
[6] Jia X,Shang L,Zhou B,et al.Generalized attribute reduct inrough set theory[J].Knowledge-Based Systems,2016,91:204-218
[7] Xu W H,Zhang W X.Methods for knowledge reduction in inconsistent ordered information systems[J].Journal of Applied Mathematics and Computing,2008,26(1):313-323
[8] Xu W H,Li Yuan,Liao Xiu-wu.Approaches to attribute reductions based on rough set and matrix computation in inconsistent ordered information systems[J].Knowledge-Based Systems,2012,7(3):78-91
[9] Inuiguchi M,Yoshioka Y.Several reducts in dominance-basedrough set approach[M]∥Interval/Probabilistic Uncertainty and Non-Classical Logics.Springer Berlin Heidelberg,2008:163-175
[10] Kusunoki Y,Inuiguchi M.A unified approach to reducts in do- minance-based rough set approach[J].Soft Computing,2010,14(5):507-515
[11] Susmaga R.Reducts and constructs in classic and dominance-based rough sets approach[J].Information Sciences,2014,271(7):45-64
[12] Du W S,Hu B Q.Approximate distribution reducts in inconsistent interval-valued ordered decision tables[J].Information Scie-nces,2014,271(7):93-114
[13] Shao M W,Zhang W X.Dominance relation and rules in an incomplete ordered information system[J].International Journal of Intelligent Systems,2005,20(1):13-27
[14] Yang X B,Yang J Y,Wu C,et al.Dominance-based rough set approach and knowledge reductions in incomplete ordered information system[J].Information Sciences,2008,178(4):1219-1234
[15] Yang X B,Yu D J,Yang J Y,et al.Dominance-based rough set approach to incomplete interval-valued information system[J].Data & Knowledge Engineering,2009,68(11):1331-1347

No related articles found!
Full text



No Suggested Reading articles found!