[1] PAWLAK Z. Rough Sets. International Journal of Computer and Information Sciences, 1982, 11(5): 341-356.
[2] PAWLAK Z. Rough Sets: Theoretical Aspects of Reasoning about Data. Dordrecht, The Netherlands:Kluwer Academic Publisher, 1991.
[3] PAWLAK Z, SKOWRON A. Rough Sets: Some Extensions. Information Sciences, 2007, 177: 28-40.
[4] BARTOL W, MIR J, PI RO K, et al. On the Coverings by To-lerance Classes. Information Sciences, 2004, 166(1/2/3/4): 193-211.
[5] QIAN Y H, LIANG J Y, YAO Y Y, et al. MGRS: A Multigranulation Rough Set. Information Sciences, 2010, 180(6): 949-970.
[6] QIAN Y H, LIANG J Y, DANG C Y. Incomplete Multigranulation Rough Set. IEEE Transactions on Systems, Man and Cybernetics(Systems and Humans), 2010, 40(2): 420-431.
[7] TAN A H, WU W Z, QIAN Y H, et al. Intuitionistic Fuzzy Rough Set-Based Granular Structures and Attribute Subset Selection. IEEE Transactions on Fuzzy Systems, 2019, 27(3): 527-539.
[8] YANG X B, LIANG S C, YU H L, et al. Pseudo-Label Neighborhood Rough Set: Measures and Attribute Reductions. International Journal of Approximate Reasoning, 2019, 105: 112-129.
[9] YAO Y Y. Relational Interpretations of Neighborhood Operators and Rough Set Approximation Operators. Information Sciences, 1998, 111(1/2/3/4): 239-259.
[10] MI J S, LEUNG Y, WU W Z. An Uncertainty Measure in Partition-Based Fuzzy Rough Sets. International Journal of General Systems, 2005, 34(1): 77-90.
[11] MI J S, LEUNG Y, WU W Z. Dependence-Space-Based Attribute Reduction in Consistent Decision Tables. Soft Computer, 2011, 15(2):
261-268.
[12] DAI J H, HU H, WU W Z, et al. Maximal-Discernibility-Pair-Based Approach to Attribute Reduction in Fuzzy Rough Sets. IEEE Transactions on Fuzzy Systems, 2018, 26(4): 2174-2187.
[13] WU W Z. Attribute Reduction Based on Evidence Theory in Incomplete Decision Systems. Information Sciences, 2008, 178(5): 1355-1371.
[14] SHE Y H, HE X L, QIAN Y H, et al. A Quantitative Approach to Reasoning about Incomplete Knowledge. Information Sciences, 2018, 451/452: 100-111.
[15] WU W Z, QIAN Y H, LI T J, et al. On Rule Acquisition in Incomplete Multi-scale Decision Tables. Information Sciences, 2017, 378: 282-302.
[16] LIN T Y, LJU Q. Rough Approximate Operators:Axiomatic Rough Set Theory // ZIARKO W P, ed. Rough Sets, Fuzzy Sets and Knowledge Discovery. Berlin, Germany:Springer, 1994: 256-260.
[17] YAO Y Y. Constructive and Algebraic Methods of the Theory of Rough Sets. Information Sciences, 1998, 109(1/2/3/4): 21-47.
[18] WU W Z, MI J S. Some Mathematical Structures of Generalized Rough Sets in Infinite Universes of Discourse // PETERS J F, SKOWRON A, CHAN C C, et al., eds. Transactions on Rough Sets XIII. Berlin, Germany: Springer-Verlag, 2011: 175-206.
[19] MI J S, LEUNG Y, ZHAO H Y, et al. Generalized Fuzzy Rough Sets Determined by a Triangular Norm. Information Sciences, 2008, 178(16): 3203-3213.
[20] WU W Z. On Some Mathematical Structures of T-Fuzzy Rough Set Algebras in Infinite Universes of Discourse. Fundamenta Informaticae, 2011, 108(3/4): 337-369.
[21] RADZIKOWSKA A M, KERRE E E. A Comparative Study of Fuzzy Rough Sets. Fuzzy Sets and Systems, 2002, 126: 137-155.
[22] WU W Z, LEUNG Y, MI J S. On Characterization of (I,T)- Fuzzy Rough Approximation Operators. Fuzzy Sets and Systems, 2005, 154(1): 76-102.
[23] MI J S, ZHANG W X. An Axiomatic Characterization of a Fuzzy Generalization of Rough Sets. Information Sciences, 2004, 160(1/2/3/4): 235-249.
[24] YEUNG D S, CHEN D G, TSANG E C C, et al. On the Generalization of Fuzzy Rough Sets. IEEE Transactions on Fuzzy Systems, 2005, 13(3): 343-361.
[25] WU W Z, LEUNG Y, SHAO M W. Generalized Fuzzy Rough Approximation Operators Determined by Fuzzy Implicators. International Journal of Approximate Reasoning. 2013, 54(9): 1388-1409.
[26] LIU G L. Axiomatic Systems for Rough Sets and Fuzzy Rough Sets. International Journal of Approximate Reasoning, 2008, 48(3): 857-867.
[27] LIU G L. Using One Axiom to Characterize Rough Set and Fuzzy Rough Set Approximations. Information Sciences, 2013, 223: 285-296.
[28] WU W Z, XU Y H, SHAO M W, et al. Axiomatic Characterizations of (S,T)-Fuzzy Rough Approximation Operators. Information Sciences, 2016, 334/335: 17-43.
[29] MA Z M, MI J S. Boundary Region-Based Rough Sets and Uncertainty Measures in the Approximation Space. Information Sciences, 2016, 370/371: 239-255. |