Computer Science

Computer Science ›› 2022, Vol. 49 ›› Issue (11A): 211100224-5.doi: 10.11896/jsjkx.211100224

• Big Data & Data Science • Previous Articles     Next Articles

Fuzzy Rough Sets Model Based on Fuzzy Neighborhood Systems

RAN Hong, HOU Ting, HE Long-yu, QIN Ke-yun   

  1. School of Mathematic,Southwest Jiaotong University,Chengdu 611756,China
  • Online:2022-11-10 Published:2022-11-21
  • About author:RAN Hong,born in 1997,postgraduate.His main research interests include rough set theory,formal concept analysis and so on.
    QIN Ke-yun,born in 1962,Ph.D,professor,Ph.D supervisor.His main research interests include rough set theory,formal concept analysis and so on.
  • Supported by:
    National Natural Science Foundation of China(61976130).

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Abstract: For fuzzy neighborhood systems,upper and lower fuzzy rough approximation operators based on general fuzzy logic operators are proposed,and the basic properties of the operators are investigated.Then,the concepts of neighborhood system of serial,reflexive,symmetric,unary and Euclidean are extended to fuzzy neighborhood systems.Finally,the related algebraic structures of fuzzy rough approximation operators are discussed when the fuzzy neighborhood system is serial,reflexive,symmetric,unary and Euclidean.

Key words: Fuzzy neighborhood system, Rough set, Upper approximation operator, Lower approximation operator

CLC Number: 

  • TP182
[1]PAWLAK Z.Rough sets[J].International Journal of Computer &Information Sciences,1982,11(5):341-356.
[2]QIAN Y H,LIANG X Y,WANG Q,et al.Local rough set:A solution to rough data analysis in big data[J].International Journal of Approximate Reasoning,2018,97:38-63.
[3]KANEIWA K,KUDO Y.A sequential pattern mining algorithm using rough set theory[J].International Journal of Approximate Reasoning,2011,52(6):881-893.
[4]WAN J H,CHEN H M,LI T R,et al.Dynamic interaction feature selection based on fuzzy rough set[J].Information Sciences,2021,581:891-911.
[5]WANG G Q,LI T R,ZHANG P F,et al.Double-local roughsets for efficient data mining[J].Information Sciences,2021,571:475-498.
[6]YAO Y Y.Constructive and algebraic methods of method theory of rough sets[J].Information Sciences,1998,109(1):21-47.
[7]YAO Y Y.Relational interpretations of neighborhood operators and approximation operators[J].Information Sciences,1998,111(1):239-259.
[8]ZHU W.Topological approaches to covering rough sets[J].Information Sciences,2007,177:1499-1508.
[9]BONIKOWSKI Z,BRYNIARSKI E,WY-BRANIEC-SKAR-DOWSKA U.Extensions and in-tentions in the rough set theory[J].Information Sciences,1998,107:149-167.
[10]YAO Y Y,YAO B X.Covering based rough set approximations[J].Information Sciences,2012,200:91-107.
[11]ZHU P,XIE H Y,WEN Q Y.A unified view of consistent functions[J].Soft Computing,2017,21(9):2189-2199.
[12]ZADEH L A.Fuzzy sets[J].Information and Control,1965,8(3):338-353.
[13]DOBOIS D,PRADE H.Rough fuzzy sets and fuzzyrough sets[J].International Journal of General System,1990,17:191-209.
[14]LIN T Y.Granular computing on binary I:data mining andneighborhood systems[M]//Rough Sets and Knowledge Disco-very.Berlin:Springer,1998:107-121.
[15]ZHAO F F,LI L Q.Axiomatization on generalized neighbor-hood system-based rough sets[J].Soft Computing,2018,22(18):6099-6110.
[16]FANG J M,CHEN P W.One-to-one corres-pondence between fuzzifying topologies and fuzzy preorders[J].Fuzzy Sets and Systems,2007,158(16):1814-1822.
[17]FANG J M,YUE Y L.K.Fan’s theorem in fuzzifying topology[J].Information Sciences,2004,162(3/4):139-146.
[18]HERRLICH H,ZHANG D X.Categorical properties of probabilistic convergence spaces[J].Applied Categorical Structures,1998,6(3):495-513.
[19]YING M S.A new approach for fuzzy topology(I)[J].Fuzzy Sets System,1991,39(3):495-513.
[20]LI L Q,JIN Q,YAO B X,et al.A rough set model based on fuzzifying neighborhood systems [J].Soft Computing,2020,24(8):6085-6099.
[21]ZHANG Y L,LI C Q,LIN M L,et al.Relationships betweengeneralized rough sets based on covering and reflexive neighborhood systems[J].Information Sciences,2015,319:56-67.
[22]LIAU C J,LIN E B,SYAU Y R.On consistent functions for neighborhood systems[J].International Journal of Approximate Reasoning,2020,121:39-58.
[23]SUN X R,LIU H W.On the constructions of t-norms on boun-ded lattices[J].Information Sciences,2021,575:173-184.
[24]GERA Z,DOMBI J.Type-2 implications on non-interactive fuzzytruth values[J].Fuzzy Sets and Systems,2008,159:3014-3032.
[25]DANA P.Prime,minimal prime and maximal ideals spaces in residuated lattices[J].Fuzzy Sets and Systems,2021,405:47-64.
[26]MA Z M,HU B Q.Topological and lattice structures of L-fuzzy rough sets determined by lower and upper sets[J].Information Sciences,2013,218:194-204.
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