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On Four Types of Multi-Covering Rough Sets

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Języki publikacji
EN
Abstrakty
EN
The generalization of Pawlak rough sets is one of the most important directions of rough set theory. In this paper, we propose four types of multi-covering rough set (MCRS) models by combining multi-granulation rough sets with covering rough sets. In the first place,We propose two types of optimistic MCRS models and study their corresponding properties, and then propose another two types of the pessimistic MCRS models and study their corresponding properties as well. Finally, the relationships among the four types of MCRS and the interrelationships between the proposed MCRS models and the existing ones listed in [8] are further investigated.
Słowa kluczowe
Wydawca
Rocznik
Strony
457--476
Opis fizyczny
Bibliogr. 53 poz.
Twórcy
autor
  • College of Applied Mathmatics, Xiamen University of Technology, Xiamen, 361024, PR China
autor
  • College of Science, Jimei University, Xiamen, 361021, PR China
Bibliografia
  • [1] EA Abo-Tabl, Rough sets and topological spaces based on similarity. Int International Journal of Machine Learning and Cybernetics, doi:10.1007/s13042-012-0107-7, 2012.
  • [2] Bonikowski Z, Bryniorski E, Wybraniec-Skardowska U. Extensions and intentions in the rough set theory. Inrormation Sciences 1998;107(1-4):149-167. doi: 10.1016/S0020-0255(97)10046-9.
  • [3] Chen DG, Wang CZ, Hu QH. A new approach to attribute reduction of consistent and inconsistent covering decision systems with covering rough sets. Information Sciences, 2007;177(17):3500-3518. doi:10.1016/j.ins.2007.02.041.
  • [4] Huang B. Intuitionistic fuzzy multigranulation spaces. Information Sciences 2014;277:299-320. Available from: http://dx.doi.org/10.1016/j.ins.2014.02.064.
  • [5] Lin GP, Liang JY, Qian YH, Multigranulation rough sets: from partition to covering. Information Sciences 2013;241:101-118. doi: 10.1016/j.ins.2013.03.046.
  • [6] Liu CH, Miao DQ. Covering rough set model based on multi-granulayions. Rough Sets, Fuzzy Sets, Data Mining and Granular Computing Volume 6743 of the series Lecture Notes in Computer Science p. 87-90, 2011. doi: 10.1007/978-3-642-21881-1_15.
  • [7] Liu CH, Wang MZ. Covering fuzzy rough set based on multi-granulation. in: Proceedings of International Conference on Uncertainty Reasoning and Knowledge Engineering, 2011;2:146-149. doi:10.1109/URKE.2011.6007930.
  • [8] Liu CH, Miao DQ, Qian J. On multi-granulation covering rough set. International Journal of Approximate Reasoning, 2014;55:1404-1418. Available from: http://dx.doi.org/10.1016/j.ijar.2014.01.002.
  • [9] Li TJ, Zhao XX, Wu W-Z. Formulation and Simplification of multi-granulation covering rough sets. Rough Sets and Intelligent Systems Paradigms Vol. 8537 of the series Lecture Notes in Computer Science, p. 135-142, 2014. doi: 10.1007/978-3-319-08729-0_12.
  • [10] Mordeson J. Rough set theory applied to (fuzzy) ideal theory. Fuzzy sets Systems 2001;121(2):315-324. doi:10.1016/S0165-0114(00)00023-3.
  • [11] Ma LW. On some types of neighborhood-related covering rough sets. International Journal of Approximate Reasoning 2012;53(6): 901-911. doi:10.1016/j.ijar.2012.03.004.
  • [12] Pawlak Z. Rough sets, International Journal of Computer and Information Sciences 1982;11(5):341-356.
  • [13] Pawlak Z. Rough Set: Theoretical Aspects of Reasoning about Data, Dordrecht: Kluwer Academic Publishers, 1991. ISBN: 978-0-7923-1472-1, 978-94-010-5564-2.
  • [14] Polkowski L, Skowron A (eds). Rough sets and current trends in computing. vol 1424 of Lecture Notes in Computer Science, Springer, Berlin, 1998. ISBN: 978-3-540-64655-6, 978-3-540-69115-0.
  • [15] Polkowski L (eds). Rough sets in knowledge discovery 1: Methodology and Applications. Studies in Fuzziness and Soft Computing vol. 18. Physica C, Heidelberg, 1998. ISBN: 978-3-7908-1884-0. doi:10.1007/978-3-7908-1883-3.
  • [16] Polkowski L, Skowron A (eds). Rough sets in knowledge discovery 2: Applications, Case Studies and Software Systems. Physica C, Heidelberg, 1998. ISBN: 3790811203, 9783790811209. doi:10.1007/978-3-7908-1883-3.
  • [17] Pomykala JA. Approximation operations in approximate space. Bulletin of the Polish Academy of Science, Mathematics 1993;18:381-396.
  • [18] Pomkala JA. On definability in the nondeterministic information system. Bulletin of the Polish Academy of Science, Mathematics 1988;36:193-210.
  • [19] Qian YH, Liang JY. Rough set method based on multi-granulations. in: proc. 5th IEEE International Conference on Cognitive Informatics, Beijing, China, July 17-19, 2006, pp. 297-304. doi:10.1109/COGINF.2006.365510.
  • [20] Qian YH, Liang YY, Yao YY, Dang CY. MGRS: A multi-granulation set. Information Sciences 2010;180:949-970. doi:10.1016/j.ins.2009.11.023.
  • [21] Skowron A, Stepaniuk J. Tolerance approximation spaces, Fundamenta Informaticae 1996;27:245–253. doi:10.3233/FI-1996-272311.
  • [22] Slowinski R, Vanderpooten D. A generalized definition of rough approximations based on similarity, IEEE Transactions on Knowledge and Data Engineering 2000;12(2):331-336. doi:10.1109/69.842271.
  • [23] Sun BZ, Ma WM. Multi-granulation rough set theory on two universes. International Journal of Intelligent and Fuzzy Systems: Applications in Engineering and Technology 2015;28(3):1251-1269. Available from: http://dx.doi.org/10.3233/IFS-141411.
  • [24] Wang J, Dai D, Zhou Z. Fuzzy covering generalized rough sets (in China). Journal of Zhoukou Teachers College 2004;21(2):20-22.
  • [25] Wu WZ, Zhang WX. Rough set approximations vs. measurable spaces. In: Granular Computing, 2006 IEEE International Conference 2006, pp.329-332. doi:10.1109/GRC.2006.1635807.
  • [26] Xu WH, Wang QR, Zhang XT. Multi granulation fuzzy rough set model on tolerance relations. in: Procssdings of the fourth International Workshop on Advanced Computational Intelligence. Wuhan, Hubei, China, October 19-21, 2006, pp. 357-364.
  • [27] Xu WH, Sun WX, Zhang XY. Multiple granulation rough set approach to ordered information systems. International Journal of General Systems 2012;41(5):475-501. Available from: http://dx.doi.org/10.1080/03081079.2012.673598.
  • [28] Xu WH, Wang QR, Luo SQ. Multi granulation fuzzy rough sets. International Journal of Intelligent and Fuzzy Systems 2014;26(3):1323-1340. doi:10.3233/IFS-130818.
  • [29] Xu WH, Wang QR, Zhang XT. Multi granulation rough sets based tolerance relations. Soft Computing 2013;17(7):1241-1252. doi:10.1007/s00500-012-0979-1.
  • [30] Xu WH, Wang QR, Zhang XT. Multi granulation fuzzy rough sets in a fuzzy tolerance approximation space. International Journal of Fuzzy Systems 2011;13 (4):246-259.
  • [31] Xu WH, Zhang XT, Wang QR. A generalized multi-granulation rough set approach. in: Bio-Inspired Computing and Applications, 7th International Conference on Intelligent Computing, ICIC 2011, Zhengzhou, China, August 11-14. 2011, vol. 6840. 2012. pp. 681-689. doi:10.1007/978-3-642-24553-4_90.
  • [32] Xu WH, Zhang WX. Measuring roughness of generalized rough sets induced by a covering. Fuzzy Sets and Systems 2007;158(22):2443-2455. doi:10.1016/j.fss.2007.03.018.
  • [33] Xu Z, Wang Q. On the properties of covering rough set model (in China). Journal of Henan Normal University 2005;33(1):130-132.
  • [34] Yang X, Song X, Chen Z, Yang J. On multigranulation rough sets in incomplete information system. International Journal of Machine Learning and Cybernetics 2012;3(3):223-232. doi:10.1007/s13042-011-0054-8.
  • [35] Yang XB, Song XN, Dou HL, Yang JY. Multi-granulation rough sets from crisp to fuzzy case. Ann Fuzzy Math Information 2011;1(1):55-70.
  • [36] Yao YY, Lin TY. Generalization of rough sets using model logic. Intelligent Automation and Soft Computing: an International Journal 1996;2(2):103-120. Available from: http://dx.doi.org/10.1080/10798587.1996.10750660.
  • [37] Yao YY. Relational interpretations of neighborhood operators and rough set approximation operators, Information Sciences 1998;111:239-259. Available from: http://dx.doi.org/10.1016/S0020-0255(98)10006-3.
  • [38] Yao YY. Constructive and algebraic methods of the theory of rough sets, Information Sciences 1998; 109:21–47. doi:10.1016/S0020-0255(98)00012-7.
  • [39] Yao YY. On generalizing rough set theory. Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing in: 9th International Conference, RSFDGrC 2003, Chongqing, China, May 2629, 2003 Proceedings. Volume 2639 of the series Lecture Notes in Computer Science, 2003, pp. 44-51. doi: 10.1007/3-540-39205-X_6.
  • [40] Yao YY, Chen Y. Subsystem based generalizations of rough set approximations. Foundations of Intelligent Systems. in: 15th International Symposium, ISMIS 2005, Saratoga Springs, NY, USA, May 25-28, 2005. Proceedings. Volume 3488 of the series Lecture Notes in Computer Science, 2005, pp. 210-218. doi:10.1007/11425274_22.
  • [41] Yao YY, She YH. Rough set models in multigranulation spaces. Information Sciences 2016;327(C):40-56. Available from: http://dx.doi.org/10.1016/j.ins.2015.08.011.
  • [42] Yao J, Liu WN. The STP model for solving imprecise problems. In: Granular Computing, 2006 IEEE International Conference 2006, pp. 683-687. doi: 10.1109/GRC.2006.1635894.
  • [43] Zakowski W. Approximations in the space (u;π), Demonstration Mathematica 1983;16:761-769.
  • [44] Zhu W, Wang FY. On three types of covering rough sets, IEEE Transactions on Knowledge Data Engineering 2007;19(8):1131-1144. doi: 10.1109/TKDE.2007.1044.
  • [45] Zhu W. Topological approaches to covering rough sets, Information Sciences 2007;177(6):1499-1508. doi:10.1016/j.ins.2006.06.009.
  • [46] Zhu W. Relationship between generalized rough sets based on binary relation and covering, Information Sciences 2009;179(3):210-225. doi:10.1016/j.ins.2008.09.015.
  • [47] Zhu W. Relationship among basic concepts in covering based rough sets, Information Sciences 2009; 179(14):2478-2486. doi:10.1016/j.ins.2009.02.013.
  • [48] Zhu W. Generalized rough sets based on relations, Information Sciences 2007;177(22): 4997-5001.
  • [49] Zhu W, Wang FY. Covering based granular computing for conflict analysis. In: Intelligence and Security Informatics. IEEE International Conference on Intelligence and Security Informatics, ISI 2006, San Diego, CA, USA, May 23-24, 2006. Proceedings. Volume 3975 of the series Lecture Notes in Computer Science pp 566-571. doi:10.1007/11760146_58.
  • [50] Zhu W, Wang SP. Matroidal approaches to generalized rough sets based on relations. International Journal of Machine Learning and Cybernetics, 2011;2(4):273-279. doi:10.1007/s13042-011-0027-y.
  • [51] Zhu P, Wen QY. Entropy and co-entropy of a covering approximation space. International Journal of Approximate Reasoning 2012;53(4):528-540. doi:10.1016/j.ijar.2011.12.004.
  • [52] Zhu P. Covering rough sets basedc on nighborhoods: an approach without using neighborhoods. International Journal of Approximate Reasoning 2011;52(3):461-472. doi:10.1016/j.ijar.2010.10.005.
  • [53] Zhang N, Yao Y, Ohshima M. Pecularity oriented multidatabasemining. IEEE Transactions on Knowledge and Data Engineering 2003;15(4):952-960. doi:10.1109/TKDE.2003.1209011.
Uwagi
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-49034ccd-9467-42a3-a4b1-bc74139bd290
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