Computer Science ›› 2014, Vol. 41 ›› Issue (12): 183-188.doi: 10.11896/j.issn.1002-137X.2014.12.040

Previous Articles     Next Articles

Adjustable Fuzzy Rough Set:Model and Attribute Reduction

SONG Jing-jing,YANG Xi-bei,QI Yong and QI Yun-song   

  • Online:2018-11-14 Published:2018-11-14

Abstract: Fuzzy rough set is an extension of classical rough set by considering requirements of the practical applications.However,many existing fuzzy rough set models only use simple fusions of a set of binary relations,and these fusions are not adjustable.To solve such problem,an adjustable fuzzy rough set was proposed by using a parameterized binary operator.Moreover,the approximate quality was regarded as a measurement and then the heuristic algorithm was used to calculate the reduction of adjustable fuzzy rough set.Finally,the approximate quality and the reduction of adjustable fuzzy rough set were compared with those of the strong fuzzy rough set and the weak fuzzy rough set respectively.The experimental results show that adjustable fuzzy rough set is a generalization of both strong and weak fuzzy rough sets.

Key words: Approximation quality,Decision system,Fuzzy rough set,Reduction

[1] Pawlak Z.Rough Sets-Theoretical Aspects of Reasoning about Data[M].Kluwer Academic Publishers,Dordrecht,Boston,London,1991
[2] Dubois D,Prade H.Rough fuzzy sets and fuzzy rough sets[J].International Journal of General Systems,1990,17:191-209
[3] Morsi N N,Yakout M M.Axiomatics for fuzzy rough sets[J].Fuzzy Sets and Systems,1998,100:327-342
[4] Mi J S,Leung Y,Zhao H Y,et al.Generalized fuzzy rough sets determined by a triangular norm[J].Information Sciences,2008,178(16):3203-3213
[5] She Y H,Wang G Y.An axiomatic approach of fuzzy rough sets based on residuated lattices[J].Computers & Mathematics with Applications,2009,58(1):189-201
[6] Chen D G,Yang Y Y,Wang H.Granular computing based onfuzzy similarity relations[J].Soft Computing,2011,15(6):1161-1172
[7] Wang C Y,Hu B Q.Fuzzy rough sets based on generalized residuated lattices[J].Information Sciences,2013,248:31-49
[8] Liu G L.Using one axiom to characterize rough set and fuzzy rough set approximations[J].Information Sciences,2013,223:285-296
[9] Hu Q H,Zhang L,Chen D G,et al.Gaussian kernel based fuzzy rough sets:Model,uncertainty measures and applications[J].International Journal of Approximate Reasoning,2010,51(4):453-471
[10] Hu Q H,Yu D R,Pedrycz W,et al.Kernelized fuzzy rough sets and their applications[J].IEEE Transactions on Knowledge and Data Engineering,2011,23(11):1649-1667
[11] He Q,Wu C X,Chen D G,et al.Fuzzy rough set based attribute reduction for information systems with fuzzy decisions[J].Knowledge-Based Systems,2011,24(5):689-696
[12] Huang B,Li H X,Wei D K.Dominance-based rough set model in intuitionistic fuzzy information systems[J].Knowledge-Based Systems,2012,28:115-123
[13] Chen D G,Kwong S,He Q,et al.Geometrical interpretation and applications of membership functions with fuzzy rough sets[J].Fuzzy Sets and Systems,2012(193):122-135
[14] Wu W Z,Leung Y,Shao M W.Generalized fuzzy rough approximation operators determined by fuzzy implicators[J].International Journal of Approximate Reasoning,2013,54(9):1388-1409
[15] Huang B,Zhang Y L,Li H X,et al.A dominance intuitionistic fuzzy-rough set approach and its applications[J].Applied Mathematical Modelling,2013,37(12/13):7128-7141
[16] Wang C Y,Hu B Q.Fuzzy rough sets based on generalized residuated lattices[J].Information Sciences,2013,248:31-49
[17] Dai J H,Tian H W,Fuzzy rough set model for set-valued data[J].Fuzzy Sets and Systems,2013,229:54-68
[18] Yao Y Q,Mi J S,Li Z J.A novel variable precision (θ,σ)-fuzzy rough set model based on fuzzy granules[J].Fuzzy Sets and Systems,2014,236:58-72
[19] Chen D G,Zhao S Y.Local reduction of decision system with fuzzy rough sets[J].Fuzzy Sets and Systems,2010,161(13):1871-1883
[20] Hu Q H,Shang A,Yu D R.Soft fuzzy rough sets for robust fea-ture evaluation and selection[J].Information Sciences,2010,180(22):4383-4400
[21] Maji P.Fuzzy-rough supervised attribute clustering algorithmand classification of microarray data[J].IEEE Transactions on Systems,Man and Cybernetics,Part B:Cybernetics,2011,41(1):222-233
[22] Chen D G,Hu Q H,Yang Y P.Parameterized attribute reduction with Gaussian kernel based fuzzy rough sets[J].Information Sciences,2011,181(23):5169-5179
[23] Chen D G,Zhang L,Zhao S Y,et al.A novel algorithm for fin-ding reducts with fuzzy rough sets[J].IEEE Transactions on Fuzzy Systems,2012,20(2):385-389
[24] Dai J H,Xu Q.Attribute selection based on information gain ratio in fuzzy rough set theory with application to tumor classification[J].Applied Soft Computing,2013,13(1):211-221
[25] 徐菲菲,魏莱,杜海洲,等.一种基于互信息的模糊粗糙集分类特征基因快速选取方法[J].计算机科学,2013,40(7):216-235
[26] 曾安平,李天瑞,罗川.高斯核模糊粗糙集中对象集变化时近似集增量更新方法研究[J].计算机科学,2013,40(7):173-177
[27] Klement E P,Mesiar R,Pap E.Triangular norms[M].Kluwer Academic Publishers,2001
[28] Yeung D S,Chen D G,Tsang E C C,et al.On the generalization of fuzzy rough sets[J].IEEE Transactions on Fuzzy Systems,2005,13(3):343-361
[29] Fung L W,Fu K S.An axiomatic approach to relational decision-making in a fuzzy environment[C]∥Zadeh L A,Fu K S,Tanaka K,et al.,eds.Fuzzy Sets and Decision Processes.New York:Academic Press,1975:227-256
[30] Qian Y H,Wu W Z,Dang C Y.Information granularity in fuzzy binary GrC model[J].IEEE Transactions on Fuzzy Systems,2011,19(2):253-264

No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!