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New categories of coverings in terms of rough fuzzy sets

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Abstract

In this article, we develop innovative models of multigranulation rough fuzzy sets, utilizing fuzzy \(\beta \)-covering and incorporating a range of techniques such as fuzzy \(\beta \)-neighborhood, fuzzy complementary \(\beta \)-neighborhood, fuzzy \(\beta \)-minimal description, and fuzzy \(\beta \)-maximal description. The axiomatic characteristics of fuzzy \(\beta \)-neighborhoods within the context of fuzzy \(\beta \)-covering based multigranulation rough fuzzy sets (F\(\beta \)CMGRFS) are analyzed. Thus, we introduce seven new classes of F\(\beta \)CMGRFS and investigate their relevant properties. Furthermore, the connections and associations between these techniques are established. Thus, we provide a set of observations and propositions that highlight the value and dissimilarities of our proposed models compared to others. A test example is produced to verify the applicability of the presented strategies and treat MCGDM issues. Finally, we compare the outcomes of our approaches and the existing studies to check the reliability and the validity of our work.

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References

  • Atef M, Khalil AM, Li SG, Azzam A, El Atik AA (2020) Comparison of six types of rough approximations based on j-neighborhood space and j-adhesion neighborhood space. J Intell Fuzzy Syst 39(3):4515–4531

    Google Scholar 

  • Atef M, Khalil AM, Li SG, Azzam A, Liu H, El Atik AA (2022) Comparison of twelve types of rough approximations based on j-neighborhood space and j-adhesion neighborhood space. Soft Comput 26:215–236

    Google Scholar 

  • Atef M, El-Atik AA (2021) Some extensions of covering-based multigranulation fuzzy rough sets from new perspectives. Soft Comput 25(8):6633–6651

    Google Scholar 

  • Atef M, Liu S (2024) Four types of grey \(\beta \) covering models and their applications. Math Comput Simul 223:108–129

    MathSciNet  Google Scholar 

  • Bonikowski Z, Bryniarski E, Wybraniec-Skardowska U (1998) Extensions and intentions in rough set theory. Inf Sci 107:149–167

    MathSciNet  Google Scholar 

  • Couso I, Dubois D (2011) Rough sets, coverings and incomplete information. Fund Inform 108(3–4):223–247

    MathSciNet  Google Scholar 

  • Dai J, Xu Q (2012) Approximations and uncertainty measures in incomplete information systems. Inf Sci 198:62–80

    MathSciNet  Google Scholar 

  • De Cock M, Cornelis C, Kerre EE (2004) Fuzzy rough sets: beyond the obvious. in: Proceedings of the 2004 IEEE International Conference on Fuzzy Systems 1:103–108

  • D’eer L, Restrepro M, Cornelis C, Gomez J (2016) Neighborhood operators for coverings based rough sets. Inf Sci 336:21–44

    Google Scholar 

  • D’eer L, Cornelis C, Godo L (2017) Fuzzy neighborhood operators based on fuzzy coverings. Fuzzy Sets Syst 312:17–35

    MathSciNet  Google Scholar 

  • Deng T, Chen Y, Xu W, Dai Q (2007) A novel approach to fuzzy rough sets based on a fuzzy covering. Inf Sci 177:2308–2326

    MathSciNet  Google Scholar 

  • Dubois D, Prade H (1990) Rough fuzzy sets and fuzzy rough sets. Int J Gen Syst 17:191–201

    Google Scholar 

  • Feng T, Zhang S, Mi J (2012) The reduction and fusion of fuzzy covering systems based on the evidence theory. Int J Approx Reason 53:87–103

    MathSciNet  Google Scholar 

  • Garg H, Atef M (2022) Cq-ROFRS: covering q-rung orthopair fuzzy rough sets and its application to multi-attribute decision-making process. Complex Intell Syst 8:2349–2370

    Google Scholar 

  • Huang B, Guo CX, Li HX, Feng GF, Zhou XZ (2016) An intuitionistic fuzzy graded covering rough set. Knowl-Based Syst 107:155–178

    Google Scholar 

  • Huang Z, Li J (2024) Covering based multi-granulation rough fuzzy sets with applications to feature selection. Expert Syst Appl 238:121908

    Google Scholar 

  • Huang Z, Li J (2024) Noise-tolerant discrimination indexes for fuzzy \(\gamma \) covering and feature subset selection. IEEE Trans Neural Netw Learn Syst 35(1):609–623

    MathSciNet  Google Scholar 

  • Huang Z, Li J, Qian Y (2022) Noise-tolerant fuzzy \(\beta \)-covering-based multigranulation rough sets and feature subset selection. IEEE Trans Fuzzy Syst 30(7):2721–2735

    Google Scholar 

  • Huang Z, Li J, Wang C (2024) Robust feature selection using multigranulation variable-precision distinguishing indicators for fuzzy covering decision systems. IEEE Trans Syst Man Cybern Syst 54(2):903–914

    Google Scholar 

  • Herawan T, Deris M, Abawajy J (2010) Rough set approach for selecting clustering attribute. Knowl-Based Syst 23:220–231

    Google Scholar 

  • Jensen R, Shen Q (2004) Semantics-preserving dimensionality reduction: rough and fuzzy-rough-based approaches. IEEE Trans Knowl Data Eng 16(12):1457–1471

    Google Scholar 

  • Li TJ, Leung Y, Zhang WX (2008) Generalized fuzzy rough approximation operators based on fuzzy covering. Int J Approx Reason 48:836–856

    MathSciNet  Google Scholar 

  • Lin G, Liang J, Qian Y (2013) Multigranulation rough sets: from partition to covering. Inf Sci 241:101–118

    MathSciNet  Google Scholar 

  • Liu GL, Zhu W (2008) The algebraic structures of generalized rough set theory. Inf Sci 178:4105–4113

    MathSciNet  Google Scholar 

  • Liu GL, Sai Y (2009) A comparison of two types of rough sets induced by coverings. Int J Approx Reason 50:521–528

    MathSciNet  Google Scholar 

  • Liu CH, Miao DQ, Qian J (2014) On multi-granulation covering rough sets. Int J Approx Reason 55(6):1404–1418

    MathSciNet  Google Scholar 

  • Ma L (2012) On some types of neighborhood related covering rough sets. Int J Approx Reason 53:901–911

    MathSciNet  Google Scholar 

  • Ma L (2016) Two fuzzy covering rough set models and their generalizations over fuzzy lattices. Fuzzy Sets Syst 294:1–17

    MathSciNet  Google Scholar 

  • Ma J, Atef M, Nada S, Nawar A (2020) Certain types of covering-based multigranulation \((I, T)\)-fuzzy rough sets with application to decision-making. Complexity 2020:6661782

    Google Scholar 

  • Ma J, Atef M, Khalil AM, Hassan N, Chen GX (2020) Novel models of fuzzy rough coverings based on fuzzy \(\alpha \)-neighborhood and its application to decision-making. IEEE Access 8:224354–224364

    Google Scholar 

  • Pawlak Z (1982) Rough sets. Int J Comput Inf Sci 11(5):341–356

    Google Scholar 

  • Pawlak Z (1985) Rough concept analysis. Bull Polish Acad Sci Math 33:9–10

    MathSciNet  Google Scholar 

  • Pomykala JA (1987) Approximation operations in approximation space. Bull Polish Acad Sci 35:653–662

    MathSciNet  Google Scholar 

  • Pomykala JA (1988) On definability in the nondeterministic information system. Bull Polish Acad Sci 36:193–210

    MathSciNet  Google Scholar 

  • Qi G, Atef M, Yang B (2024) Fermatean fuzzy covering-based rough sets and their applications in multi-attribute decision-making. Eng Appl Artif Intell 127:107181

    Google Scholar 

  • Qian YH, Liang JY, Yao YY, Dang CY (2010) MGRS: a multi-granulation rough set. Inf Sci 180:949–970

    MathSciNet  Google Scholar 

  • Tsang ECC, Chen D, Yeung DS (2008) Approximations and reducts with covering generalized rough sets. Comput Math Appl 56:279–289

    MathSciNet  Google Scholar 

  • Wei W, Liang J, Qian Y (2012) A comparative study of rough sets for hybrid data. Inf Sci 190:1–16

    MathSciNet  Google Scholar 

  • Wu W, Zhang W (2002) Neighborhood operator systems and approximations. Inf Sci 144:263–282

    MathSciNet  Google Scholar 

  • Xu WH, Zhang WX (2007) Measuring roughness of generalized rough sets induced a covering. Fuzzy Sets Syst 158:2443–2455

    MathSciNet  Google Scholar 

  • Xu WH, Wang QR, Zhang XT (2011) Multi-granulation fuzzy rough sets in a fuzzy tolerance approximation space. Int J Fuzzy Syst 13(4):246–259

    MathSciNet  Google Scholar 

  • Yang XB, Qian YH, Yang J (2012) Hierarchical structures on multigranulation spaces. J Comput Sci Technol 27(6):1169–1183

    MathSciNet  Google Scholar 

  • Yang B, Hu BQ (2017) On some types of fuzzy covering based rough sets. Fuzzy Sets Syst 312:36–65

    MathSciNet  Google Scholar 

  • Yang B, Hu BQ (2019) Fuzzy neighborhood operators and derived fuzzy coverings. Fuzzy Sets Syst 370:1–33

    MathSciNet  Google Scholar 

  • Yang B (2022) Fuzzy covering-based rough set on two different universes and its application. Artif Intell Rev 55(6):4717–4753

    Google Scholar 

  • Yang B, Atef M (2023) Novel classes of fuzzy \(\beta \)-covering-based rough set over two distinct universes. Fuzzy Sets Syst 461:108350

    MathSciNet  Google Scholar 

  • Yao YY (1998) Relational interpretations of neighborhood operators and rough set approximation operators. Inf Sci 111:239–259

    MathSciNet  Google Scholar 

  • Yao YY, Yao B (2012) Covering based rough set approximations. Inf Sci 200:91–107

    MathSciNet  Google Scholar 

  • Zadeh LA (1996) Fuzzy sets. Fuzzy sets, fuzzy logic, and fuzzy systems: selected papers by Lotfi A Zadeh. World Scientific, Singapore, pp 394–432

    Google Scholar 

  • Zhan J, Sun B (2020) Covering-based intuitionistic fuzzy rough sets and applications in multi-attribute decision-making. Artif Intell Rev 53(1):671–701

    Google Scholar 

  • Zhan J, Zhang X, Yao Y (2020) Covering based multigranulation fuzzy rough sets and corresponding applications. Artif Intell Rev 53:1093–1126

    Google Scholar 

  • Zhan J, Sun B, Alcantud JCR (2019) Covering based multigranulation \((I, T)\)-fuzzy rough set models and applications in multi-attribute group decision-making. Inf Sci 476:290–318

    MathSciNet  Google Scholar 

  • Zhan J, Sun B, Zhang X (2020) PF-TOPSIS method based on CPFRS models: an application to unconventional emergency events. Comput Ind Eng 139:106192

    Google Scholar 

  • Zhan J, Xu W (2020) Two types of coverings based multigranulation rough fuzzy sets and applications to decision making. Artif Intell Rev 53(1):167–198

    Google Scholar 

  • Zhang C, Ding J, Li D, Zhan J (2021) A novel multi-granularity three-way decision-making approach in q-rung orthopair fuzzy information systems. Int J Approx Reason 138:161–187

    MathSciNet  Google Scholar 

  • Zhang C, Ding J, Zhan J, Li D (2022) Incomplete three-way multi-attribute group decision making based on adjustable multigranulation Pythagorean fuzzy probabilistic rough sets. Int J Approx Reason 147:40–59

    MathSciNet  Google Scholar 

  • Zhang K, Zhan J, Wu W (2020) On multi-criteria decision-making method based on a fuzzy rough set model with fuzzy \(\alpha \)-neighborhoods. IEEE Trans Fuzzy Syst 29(9):2491–2505

    Google Scholar 

  • Zhu W (2007) Topological approaches to covering rough sets. Inf Sci 177:1499–1508

    MathSciNet  Google Scholar 

  • Zhu W (2009) Relationship between generalized rough sets based on binary relation and covering. Inf Sci 179(3):210–225

    MathSciNet  Google Scholar 

  • Zhu W, Wang F (2003) Reduction and axiomization of covering generalized rough sets. Inf Sci 152:217–230

    MathSciNet  Google Scholar 

  • Zhu W, Wang F (2007) On three types of covering rough sets. IEEE Trans Knowl Data Eng 19:1131–1144

    Google Scholar 

  • Zhu W, Wang F (2012) The fourth types of covering-based rough sets. Inf Sci 201:80–92

    MathSciNet  Google Scholar 

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Correspondence to Mohammed Atef.

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Atef, M. New categories of coverings in terms of rough fuzzy sets. Comp. Appl. Math. 43, 378 (2024). https://doi.org/10.1007/s40314-024-02882-5

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