Abstract Multi-granulation rough set method (MGRS) is one of new directions in rough set theory. It is a data modeling method in the context of multiple granular spaces. Firstly, a concept of distribution reduction is introduced to pessimistic multi-granulation rough model, and a granular space selection under multiple granular spaces is investigated. Then, the important measure of a granular space in this model is defined, and an algorithm is designed to obtain a granular space reduction in the pessimistic multi-granulation rough model. Finally, an example is employed to verify the validity of the proposed algorithm. The obtained results are much closer to the practical decision.
[1] Pawlak Z.Rough Sets: Theoretical Aspects of Reasoning about Data,System Theory,Knowledge Engineering and Problem Solving.Dordrecht,Netherlands: Kluwer,1991 [2] Pawlak Z,Skowron A.Rudiments of Rough Sets.Information Sciences,2007,177(1): 3-27 [3] Duntsch I,Gediga G.Uncertainty Measures of Rough Set Prediction.Artificial Intelligence,1998,106(1): 109-137 [4] Jensen R,Shen Qiang.Fuzzy-Rough Sets Assisted Attribute Selec- tion.IEEE Trans on Fuzzy Systems,2007,15(1): 73-89 [5] Jeon G,Kim D,Jeong J.Rough Sets Attributes Reduction Based Expert System in Interlaced Video Sequences.IEEE Trans on Consumer Electronics,2006,52(4): 1348-1355 [6] Liang Jiye,Chin K S.A New Method for Measuring Uncertainty and Fuzziness in Rough Set Theory.International Journal of General Systems,2002,31(4): 331-342 [7] Qian Yuhua,Liang Jiye,Dang Chuanyin.Incomplete Multigranulation Rough Set.IEEE Trans on Systems,Man and Cybernetics,2010,40(2): 420-431 [8] Qian Yuhua,Liang Jiye,Li Deyu,et al.Approximation Reduction in Inconsistent Incomplete Decision Tables.Knowledge-Based Systems,2010,23(2): 427-433 [9] Xu Z B,Liang J Y,Dang C Y,et al.Inclusion Degree: A Perspective on Measures for Rough Set Data Analysis.Information Sciences,2002,141(3/4): 227-236 [10] Ziarko W.Variable Precision Rough Sets Model.Journal of Computer System Science,1993,46(1): 39-59 [11] Slezak D,Ziarko W.The Investigation of the Bayesian Rough Set Model.International Journal of Approximate Reasoning,2005,40(1/2): 81-91 [12] Zadeh L A.Toward a Theory of Fuzzy Information Granulation and Its Centrality in Human Reasoning and Fuzzy Logic.Fuzzy Sets and Systems,1997,90(2): 111-127 [13] Liang Jiye,Li Deyu.Uncertainty and Knowledge Acquisition in Information Systems.Beijing,China: Science Press,2005 (in Chinese) (梁吉业,李德玉.信息系统中的不确定性与知识获取.北京:科学出版社,2005) [14] Qian Yuhua,Liang Jiye,Yao Yiyu,et al.MGRS: A Multi-Granulation Rough Set.Information Sciences,2010,180(6): 949-970 [15] Qian Yuhua,Liang Jiye,Wei Wei.Pessimistic Rough Decision // Proc of the 2nd International Workshop on Rough Sets Theory.Zhoushan,China,2010: 440-449 [16] Kryszkie M.Comparative Studies of Alternative Type of Knowledge Reduction in Inconsistent Systems.International Journal of Intelligent Systems,2001,16(1): 105-120 [17] Zhang Wenxiu,Mi Jusheng,Wu Weizhi.Knowledge Reduction in Inconsistent Information Systems.Chinese Journal of Computers,2003,26(1): 12-18(in Chinese) (张文修,米据生,吴伟志.不协调目标信息系统的知识约简.计算机学报,2003,26(1): 12-18)
2012, Vol. 25 
