Pessimistic rough set based decisions: A multigranulation fusion strategy

Information Sciences

Volumn 264, Issue , 2014, Pages 196-210

  Qian, Yuhua ^a   Li, Shunyong ^a   Liang, Jiye ^a   Shi, Zhongzhi ^b   Wang, Feng ^a  

^a SHANXI UNIVERSITY   (China)

^b INSTITUTE OF COMPUTING TECHNOLOGY   (China)

Author keywords

Attribute reduction; Granular computing; Multigranulation; Pessimistic rough set based decision; Rough set

Indexed keywords

EID: 84894439092     PISSN: 00200255     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ins.2013.12.014     Document Type: Article

References (45)

1. D. Dubois, and H. Prade Rough fuzzy sets and fuzzy rough sets Int. J. Gen. Syst. 17 1990 191 209
2. I. Düntsch, and G. Gediga Uncertainty measures of rough set prediction Artif. Intell. 106 1998 109 137
3. T.F. Fan, C.J. Liau, and D.R. Liu Dominance-based fuzzy rough set analysis of uncertain and possibilistic data tables Int. J. Approx. Reason. 52 9 2011 1283 1297
4. T. Feng, S.P. Zhang, and J.S. Mi The reduction and fusion of fuzzy covering systems based on the evidence theory Int. J. Approx. Reason. 53 1 2012 87 103
5. G. Gediga, and I. Düntsch Rough approximation quality revisited Artif. Intell. 132 2001 219 234
6. J.W. Guan, and D.A. Bell Rough computational methods for information systems Artif. Intell. 105 1998 77 103
7. J.P. Herbert, and J.T. Yao Game-theoretic rough sets Fundam. Inform. 108 3-4 2011 267 286
8. J.P. Herbert, J.T. Yao, Analysis of data-driven paramenters in game-theoretic rough sets, in: Proceedings of International Conference on Rough Sets and Knowledge Technology, Banff, Canada, LNCS, vol. 6954, 2011, pp. 447-456.
9. X.Y. Jia, W.W. Li, L. Shang, J.J. Chen, An optimization viewpoint of decision-theoretic rough set model, in: Proceedings of International Conference on Rough Sets and Knowledge Technology, Banff, Canada, LNCS, vol. 6954, 2011, pp. 457-465.
10. R. Jensen, and Q. Shen Fuzzy-rough sets assisted attribute selection IEEE Trans. Fuzzy Syst. 15 1 2007 73 89
11. G. Jeon, D. Kim, and J. Jeong Rough sets attributes reduction based expert system in interlaced video sequences IEEE Trans. Consum. Electr. 52 4 2006 1348 1355
12. M. Kryszkiewicz Rough set approach to incomplete information systems Inform. Sci. 112 1998 39 49
13. M. Kryszkiewicz Rules in incomplete information systems Inform. Sci. 113 1999 271 292
14. Y. Leung, and D.Y. Li Maximal consistent block technique for rule acquisition in incomplete information systems Inform. Sci. 153 2003 85 106
15. H.X. Li, M.H. Wang, X.Z. Zhou, and j.B. Zhao An interval set model for learning rules from incomplete information table Int. J. Approx. Reason. 53 1 2012 24 37
16. J.Y. Liang, C.Y. Dang, K.S. Chin, and C.M. Yam Richard A new method for measuring uncertainty and fuzziness in rough set theory Int. J. Gen. Syst. 31 4 2002 331 342
17. J.Y. Liang, and D.Y. Li Uncertainty and Knowledge Acquisition in Information Systems 2005 Science Press Beijing, China
18. J.Y. Liang, and Y.H. Qian Information granules and entropy theory in information systems Sci. China-Ser. F: Inform. Sci. 51 10 2008 1427 1444
19. G.L. Liu Using one axiom to characterize rough set and fuzzy rough set approximations Inform. Sci. 223 2013 285 296
20. Z. Pawlak Rough sets: theoretical aspects of reasoning about data, system theory Knowledge Engineering and Problem Solving vol. 9 1991 Kluwer Dordrecht
21. Z. Pawlak, and A. Skowron Rudiments of rough sets Inform. Sci. 177 2007 3 27
22. W. Pedrycz Granular Computing: Analysis and Design of Intelligent Systems 2013 CRC Press/Francis Taylor Boca Raton
23. Y.H. Qian, H. Zhang, Y.L. Sang, and J.Y. Liang Multigranulation decision-theoretic rough sets Int. J. Approx. Reasoa. 2013 http://dx.doi.org/10. 1016/j.ijar.2013.03.004
24. Y.H. Qian, C.Y. Dang, J.Y. Liang, MGRS in incomplete information systems, in: Proceedings of 2007 IEEE Conference on Granular Computing, 2007, pp. 163-168.
25. Y.H. Qian, J.Y. Liang, and C.Y. Dang Incomplete multigranulation rough set IEEE Trans. Syst. Man Cybern.-Part A 20 2010 420 431
26. Y.H. Qian, J.Y. Liang, D.Y. Li, F. Wang, and N.N. Ma Approximation reduction in inconsistent incomplete decision tables Knowl.-Based Syst. 23 2010 427 433
27. Y.H. Qian, J.Y. Liang, W. Pedrycz, and C.Y. Dang Positive approximation: an accelerator for attribute reduction in rough set theory Artif. Intell. 174 2010 597 618
28. Y.H. Qian, J.Y. Liang, W. Wei, Pessimistic rough decision, in: Second International Workshop on Rough Sets Theory, 19-21, October 2010, Zhoushan, PR China, pp. 440-449.
29. Y.H. Qian, J.Y. Liang, Y.Y. Yao, and C.Y. Dang MGRS: a multi-granulation rough set Inform. Sci. 180 2010 949 970
30. M. Rebolledo Rough intervals-enhancing intervals f or qualitative modeling of technical systems Artif. Intell. 170 2006 667 685
31. Q. Shen, and A. Chouchoulas A rough-fuzzy approach for generating classification rules Pattern Recogn. 35 2002 2425 2438
32. D. Ślezak, and W. Ziarko The investigation of the Bayesian rough set model Int. J. Approx. Reason. 40 2005 81 91
33. W. Wei, J.Y. Liang, Y.H. Qian, and C.Y. Dang Can fuzzy entropies be effective measures for evaluating the roughness of a rough set? Inform. Sci. 232 2013 143 166
34. Z.B. Xu, J.Y. Liang, C.Y. Dang, and K.S. Chin Inclusion degree: a perspective on measures for rough set data analysis Inform. Sci. 141 2002 227 236
35. X.P. Yang, H.G. Song, T.J. Li, Decision making in incomplete information systems based on decision-theoretic rough sets, in: Proceedings of International Conference on Rough Sets and Knowledge Technology, Banff, Canada, LNCS, vol. 6954, 2011, pp. 495-503.
36. J.T. Yao, J.T. Yao, Y.Y. Yao, and W. Ziarko Probabilistic rough sets: approximations, decision-makings, and applications Int. J. Approx. Reason. 49 2008 253 254
37. Y.Y. Yao The superiority of three-way decisions in probabilistic rough set models Inform. Sci. 181 2011 1080 1096
38. Y.Y. Yao Information granulation and rough set approximation Int. J. Intell. Syst. 16 2001 87 104
39. Y.Y. Yao Three-way decisions with probabilistic rough sets Inform. Sci. 180 2010 341 353
40. L.A. Zadeh Toward a theory of fuzzy information granulation and its centrality in human reasoning and fuzzy logic Fuzzy Sets Syst. 90 1997 111 127
41. A. Zeng, D. Pan, Q.L. Zheng, and H. Peng Knowledge acquisition based on rough set theory and principal component analysis IEEE Intell. Syst. 2006 78 85
42. X.Y. Zhang, Z.W. Mo, F. Xiong, and W. Cheng Comparative study of variable precision rough set model and graded rough set model Int. J. Approx. Reason. 53 1 2012 104 116
43. Y.L. Zhang, and M.K. Luo Relationships between covering-based rough sets and relation-based rough sets Inform. Sci. 225 2013 55 71
44. S.Y. Zhao, Eric. C.C. Tsang, and D.G. Chen The model of fuzzy variable rough sets IEEE Trans. Fuzzy Syst. 17 2 2009 451 467
45. W. Ziarko Variable precision rough sets model J. Comput. Syst. Sci. 46 1 1993 39 59