[１] Pawlak Z. Rough set[J]. Inter J Comput Info Sci,1982,11:341-356.
[2]
[２] Kryszkiewicz M. Rough set approach to incomplete information systems[J]. Info Sci,1998,112:39-49.
[3]
[３] Kryszkiewicz M. Rules in incomplete information systems[J]. Info Sci,1999,113:271-292.
[4]
[４] Leung Y, Li D Y. Maximal consistent block technique for rule acquisition in incomplete information systems[J]. Info Sci,2003,153:85-106.
[5]
[５] Guan Yan-yong, Wang Hong-kai. Set-valued information systems[J]. Info Sci,2006,176:2507-2525.
[6]
[６] Greco S, Matarazzo B, Slowinski R. Rough sets theory for multicriteria decision analysis[J]. Euro J Oper Res,2001,129:1-47.
[7]
[７] Kim D. Data classification based on tolerant rough set[J]. Pattern Recognition,2001,34:1613-1624.
[8]
[８] Yang Xi-bei, Yang Jing-yu, Wu Chen, et al. Dominance-based rough set approach and knowledge reductions in incomplete ordered information system[J]. Info Sci,2008,178:1219-1234.
[9]
[９] Slowinski R, Vanderpooten D. A generalized definition of rough approximations based on similarity[J]. IEEE Trans Knowledge and Data Engineering,2000,12:331-336.
[10]
Qin Ke-yun, Yang Ji-lin, Pei Zheng. Generalized rough sets based on reflexive and transitive relations[J]. Info Sci,2008,178:4138-4141.
[11]
Gong Zeng-tai, Sun Bing-zhen, Chen De-gang. Rough set theory for the interval-valued fuzzy information systems[J]. Info Sci,2008,178:1968-1985.
[12]
Qian Yu-hua, Liang Ji-ye, Dang Chuang-yin. Interval ordered information systems[J]. Comput Math Appl,2008,56:1994-2009.
