A multigranulation rough set over two universes delivers a unique perspective on the combination of multigranulation information. This paper presents the pessimistic multignualtion rough set over dual universes based on soft binary relations. Firstly, a new pessimistic multigranualtion rough set over dual universes based on two soft binary relations has been developed, and their properties are derived. Then we extend this idea and present pessimistic multigranulation roughness over dual universes based on the finite number of soft binary relations. Finally, we present an example to illustrate our proposed multigranualtion rough set model.
Citation: Jamalud Din, Muhammad Shabir, Samir Brahim Belhaouari. A novel pessimistic multigranulation roughness by soft relations over dual universe[J]. AIMS Mathematics, 2023, 8(4): 7881-7898. doi: 10.3934/math.2023397
A multigranulation rough set over two universes delivers a unique perspective on the combination of multigranulation information. This paper presents the pessimistic multignualtion rough set over dual universes based on soft binary relations. Firstly, a new pessimistic multigranualtion rough set over dual universes based on two soft binary relations has been developed, and their properties are derived. Then we extend this idea and present pessimistic multigranulation roughness over dual universes based on the finite number of soft binary relations. Finally, we present an example to illustrate our proposed multigranualtion rough set model.
[1] | A. Ali, M. I. Ali, N. Rehman, New types of dominance based multi-granulation rough sets and their applications in conflict analysis problems, J. Intell. Fuzzy Syst., 35 (2018), 3859–3871. https://doi.org/10.3233/JIFS-18757 doi: 10.3233/JIFS-18757 |
[2] | M. I. Ali, A note on soft sets, rough soft sets and fuzzy soft sets, Appl. Soft Comput., 11 (2011), 3329–3332. https://doi.org/10.1016/j.asoc.2011.01.003 doi: 10.1016/j.asoc.2011.01.003 |
[3] | S. Ayub, W. Mahmood, M. Shabir, A. N. Koam, R. Gul, A study on soft multi-granulation rough sets and their applications, IEEE Access, 2022. https://doi.org/10.1109/ACCESS.2022.3218695 doi: 10.1109/ACCESS.2022.3218695 |
[4] | D. G. Chen, C. Z. Wang, Q. H. Hu, A new approach to attribute reduction of consistent and inconsistent covering decision systems with covering rough sets, Inform. Sci., 177 (2007), 3500–3518. https://doi.org/10.1016/j.ins.2007.02.041 doi: 10.1016/j.ins.2007.02.041 |
[5] | J. Din, M. Shabir, Y. Wang, Pessimistic multigranulation roughness of a fuzzy set based on soft binary relations over dual universes and its application, Mathematics, 10 (2022), 541. https://doi.org/10.3390/math10040541 doi: 10.3390/math10040541 |
[6] | F. Feng, M. I. Ali, M. Shabir, Soft relations applied to semigroups, Filomat, 27 (2013), 1183–1196. https://doi.org/10.2298/FIL1307183F doi: 10.2298/FIL1307183F |
[7] | F. Feng, X. Liu, V. Leoreanu-Fotea, Y. B. Jun, Soft sets and soft rough sets, Inform. Sci., 181 (2011), 1125–113. https://doi.org/10.1016/j.ins.2010.11.004 doi: 10.1016/j.ins.2010.11.004 |
[8] | S. Greco, B. Matarazzo, R. Slowinski, Rough approximation by dominance relations, Int. J. Intell. Syst., 17 (2002), 153–171. https://doi.org/10.1002/int.10014 doi: 10.1002/int.10014 |
[9] | B. Huang, C. Guo, Y. Zhuang, H. Li, X. Zhou, Intuitionistic fuzzy multigranulation rough sets, Inform. Sci., 277 (2014), 299–320. https://doi.org/10.1016/j.ins.2014.02.064 doi: 10.1016/j.ins.2014.02.064 |
[10] | Z. Li, N. Xie, N. Gao, Rough approximations based on soft binary relations and knowledge bases, Soft Comput., 21 (2017), 839–852. https://doi.org/10.1007/s00500-016-2077-2 doi: 10.1007/s00500-016-2077-2 |
[11] | T. J. Li, Y. Leung, W. X. Zhang, Generalized fuzzy rough approximation operators based on fuzzy coverings, Int. J. Approx. Reason., 48 (2008), 836–856. https://doi.org/10.1016/j.ijar.2008.01.006 doi: 10.1016/j.ijar.2008.01.006 |
[12] | Z. Li, N. Xie, N. Gao, Rough approximations based on soft binary relations and knowledge bases, Soft Comput., 21 (2017), 839–852. https://doi.org/10.1007/s00500-016-2077-2 doi: 10.1007/s00500-016-2077-2 |
[13] | G. Liu, Rough set theory based on two universal sets and its applications, Knowl.-Based Syst., 23 (2010), 110–115. https://doi.org/10.1016/j.knosys.2009.06.011 doi: 10.1016/j.knosys.2009.06.011 |
[14] | C. Liu, D. Miao, N. Zhang, Graded rough set model based on two universes and its properties, Knowl.-Based Syst., 33 (2012), 65–72. https://doi.org/10.1016/j.knosys.2012.02.012 doi: 10.1016/j.knosys.2012.02.012 |
[15] | D. Molodtsov. Soft set theory—first results, Comput. Math. Appl., 37 (1999), 19–31. |
[16] | W. Ma, B. Sun, Probabilistic rough set over two universes and rough entropy, Int. J. Approx. Reason., 53 (2012), 608–619. https://doi.org/10.1016/j.ijar.2011.12.010 doi: 10.1016/j.ijar.2011.12.010 |
[17] | Z. Pawlak, Rough sets, Int. J. Comput. Inform. Sci., 11 (1982), 341–356. https://doi.org/10.1007/BF01001956 doi: 10.1007/BF01001956 |
[18] | Z. Pawlak, Rough sets: Theoretical aspects of reasoning about data, Springer Science and Business Media, 2012. |
[19] | Y. Qian, J. Liang, Y. Yao, C. Dang, MGRS: A multi-granulation rough set, Inform. Sci., 180 (2010), 949–970. https://doi.org/10.1016/j.ins.2009.11.023 doi: 10.1016/j.ins.2009.11.023 |
[20] | Y. Qian, J. Liang, C. Dang, Incomplete multigranulation rough set, IEEE T. Syst. Man Cy., 40 (2009), 420–431. https://doi.org/10.1109/TSMCA.2009.2035436 doi: 10.1109/TSMCA.2009.2035436 |
[21] | M. Shabir, M. I. Ali, T. Shaheen, Another approach to soft rough sets, Knowl.-Based Syst., 40 (2013), 72–80. https://doi.org/10.1016/j.knosys.2012.11.012 doi: 10.1016/j.knosys.2012.11.012 |
[22] | M. Shabir, J. Din, I. A. Ganie, Multigranulation roughness based on soft relations, J. Intell. Fuzzy Syst., 40 (2021), 10893–10908. https://doi.org/10.3233/JIFS-201910 doi: 10.3233/JIFS-201910 |
[23] | M. Shabir, R. S. Kanwal, M. I. Ali, Reduction of an information system, Soft Comput., 24 (2020), 10801–10813. https://doi.org/10.1007/s00500-019-04582-3 doi: 10.1007/s00500-019-04582-3 |
[24] | A. Skowron, J. Stepaniuk, Tolerance approximation spaces, Fund. Inform., 27 (1996), 245–253. https://doi.org/10.3233/FI-1996-272311 doi: 10.3233/FI-1996-272311 |
[25] | R. Slowinski, D. Vanderpooten, A generalized definition of rough approximations based on similarity, IEEE T. Knowl. Data Eng., 12 (2000), 331–336. https://doi.org/10.1109/69.842271 doi: 10.1109/69.842271 |
[26] | B. Sun, W. Ma, Multigranulation rough set theory over two universes, J. Intell. Fuzzy Syst., 28 (2015), 1251–1269. https://doi.org/10.3233/IFS-141411 doi: 10.3233/IFS-141411 |
[27] | B. Sun, W. Ma, X. Xiao, Three-way group decision making based on multigranulation fuzzy decision-theoretic rough set over two universes, Int. J. Approx. Reason., 81 (2017), 87–102. https://doi.org/10.1016/j.ijar.2016.11.001 doi: 10.1016/j.ijar.2016.11.001 |
[28] | B. Sun, W. Ma, Y. Qian, Multigranulation fuzzy rough set over two universes and its application to decision making, Knowl.-Based Syst., 123 (2017), 61–74. https://doi.org/10.1016/j.knosys.2017.01.036 doi: 10.1016/j.knosys.2017.01.036 |
[29] | B. Sun, W. Ma, X. Chen, X. Zhang, Multigranulation vague rough set over two universes and its application to group decision making, Soft Comput., 23 (2019), 8927–8956. https://doi.org/10.1007/s00500-018-3494-1 doi: 10.1007/s00500-018-3494-1 |
[30] | B. Sun, X. Zhou, N. Lin, Diversified binary relation-based fuzzy multigranulation rough set over two universes and application to multiple attribute group decision making, Inform. Fusion, 55 (2020), 91–104. https://doi.org/10.1016/j.inffus.2019.07.013 doi: 10.1016/j.inffus.2019.07.013 |
[31] | B. Sun, W. Ma, X. Chen, X. Zhang, Multigranulation vague rough set over two universes and its application to group decision making, Soft Comput., 23 (2019), 8927–8956. https://doi.org/10.1007/s00500-018-3494-1 doi: 10.1007/s00500-018-3494-1 |
[32] | B. Sun, W. Ma, Multigranulation rough set theory over two universes, J. Intell. Fuzzy Syst., 28 (2015), 1251–1269. https://doi.org/10.3233/IFS-141411 doi: 10.3233/IFS-141411 |
[33] | A. Tan, W. Z. Wu, S. Shi, S. Zhao, Granulation selection and decision making with multigranulation rough set over two universes, Int. J. Mach. Learn. Cyb., 10 (2019), 2501–2513. https://doi.org/10.1007/s13042-018-0885-7 doi: 10.1007/s13042-018-0885-7 |
[34] | Y. H. Qian, J. Y. Liang, W. Wei, Pessimistic rough decision, The Second International Workshop on Rough Set Theory, 005 (2010), 440–449. |
[35] | W. Z. Wu, W. X. Zhang, Neighborhood operator systems and approximations, Inform. Sci., 144 (2002), 201–217. https://doi.org/10.1016/S0020-0255(02)00180-9 doi: 10.1016/S0020-0255(02)00180-9 |
[36] | W. Z. Wu, J. S. Mi, W. X. Zhang, Generalized fuzzy rough sets, Inform. Sci., 151 (2003), 263–282. https://doi.org/10.1016/S0020-0255(02)00379-1 doi: 10.1016/S0020-0255(02)00379-1 |
[37] | W. Xu, W. Li, X. Zhang, Generalized multigranulation rough sets and optimal granularity selection, Granular Comput., 2 (2017), 271–288. https://doi.org/10.1007/s41066-017-0042-9 doi: 10.1007/s41066-017-0042-9 |
[38] | W. H. Xu, W. X. Zhang, Measuring roughness of generalized rough sets induced by a covering, Fuzzy Set. Syst., 158 (2007), 2443–2455. https://doi.org/10.1016/j.fss.2007.03.018 doi: 10.1016/j.fss.2007.03.018 |
[39] | W. Xu, X. Zhang, Q. Wang, S. Sun, On general binary relation based rough set, J. Inform. Comput. Sci., 7 (2012), 54–66. |
[40] | W. Xu, Q. Wang, S. Luo, Multi-granulation fuzzy rough sets, J. Intell. Fuzzy Syst., 26 (2014), 1323–1340. https://doi.org/10.3233/IFS-130818 doi: 10.3233/IFS-130818 |
[41] | Y. Y. Yao, T. T. Lin, Generalization of rough sets using mo dal logic, Intell. Autom. Soft Comput., 2 (1996), 103–120. |
[42] | Y. Y. Yao, Generalized rough set models, Rough Set. Knowl. Discov., 1 (1998), 286–318. |
[43] | Y. Yao, B. Yao, Covering based rough set approximations, Inform. Sci., 200 (2012), 91–107. https://doi.org/10.1016/j.ins.2012.02.065 doi: 10.1016/j.ins.2012.02.065 |
[44] | X. B. Yang, X. N. Song, H. L. Dou, J. Y. Yang, Multi-granulation rough set: From crisp to fuzzy case, Ann. Fuzzy Math. Inform., 1 (2011), 55–70. |
[45] | R. Yan, J. Zheng, J. Liu, Y. Zhai, Research on the model of rough set over dual-universes, Knowl.-Based Syst., 23 (2010), 817–822. https://doi.org/10.1016/j.knosys.2010.05.006 doi: 10.1016/j.knosys.2010.05.006 |
[46] | W. Zhu, Generalized rough sets based on relations, Inform. Sci., 177 (2007), 4997–5011. https://doi.org/10.1016/j.ins.2007.05.037 doi: 10.1016/j.ins.2007.05.037 |
[47] | W. Zhu, Relationship between generalized rough sets based on binary relation and covering, Inform. Sci., 179 (2009) 210–225. https://doi.org/10.1016/j.ins.2008.09.015 doi: 10.1016/j.ins.2008.09.015 |
[48] | Q. Zhou, Research on tolerance-based rough set models, In 2010 International Conference on System Science, Engineering Design and Manufacturing Informatization, IEEE, Yichang, China, 2 (2010), 137–139. https://doi.org/10.1109/ICSEM.2010.124 |
[49] | J. Zhan, W. Xu, Two types of coverings based multigranulation rough fuzzy sets and applications to decision making, Artif. Intell. Rev., 53 (2020), 167–198. https://doi.org/10.1007/s10462-018-9649-8 doi: 10.1007/s10462-018-9649-8 |
[50] | Q. Zhang, Q. Xie, G. Wang, A survey on rough set theory and its applications, CAAI T. Intell. Techno., 1 (2016), 323–333. https://doi.org/10.1016/j.trit.2016.11.001 doi: 10.1016/j.trit.2016.11.001 |
[51] | J. Zhan, X. Zhang, Y. Yao, Covering based multigranulation fuzzy rough sets and corresponding applications, Artif. Intell. Rev., 53 (2020), 1093–1126. https://doi.org/10.1007/s10462-019-09690-y doi: 10.1007/s10462-019-09690-y |
[52] | C. Zhang, D. Li, R. Ren, Pythagorean fuzzy multigranulation rough set over two universes and its applications in merger and acquisition, Int. J. Intell. Syst., 31 (2016), 921–943. https://doi.org/10.1002/int.21811 doi: 10.1002/int.21811 |
[53] | H. Y. Zhang, W. X. Zhang, W. Z. Wu, On characterization of generalized interval-valued fuzzy rough sets on two universes of discourse, Int. J. Approx. Reason., 51 (2009), 56–70. https://doi.org/10.1016/j.ijar.2009.07.002 doi: 10.1016/j.ijar.2009.07.002 |
[54] | C. Zhang, D. Li, Y. Mu, D. Song, An interval-valued hesitant fuzzy multigranulation rough set over two universes model for steam turbine fault diagnosis, Appl. Math. Model., 42 (2017), 693–704. https://doi.org/10.1016/j.apm.2016.10.048 doi: 10.1016/j.apm.2016.10.048 |