Abstract
Axiomatization is a significant and challenging task in the field of fuzzy variable precision rough sets, where research is currently limited. This paper aims to address this gap by defining and characterizing 14 types of L-fuzzy variable precision rough sets (LFVPRS for short). First, we introduce three fundamental LFVPRSs generated by Euclidean, mediate, and associate L-fuzzy relations. Second, we present their single axiomatic characterizations using the product of L-fuzzy sets. Lastly, we provide single axiomatic characterizations for another 11 types of LFVPRSs, which are generated by various compositions of reflexive, transitive, symmetry, Euclidean, mediate, and associate L-fuzzy relations. These single axiomatic characterizations are entirely innovative and have not been explored, even in the context of classical rough sets and fuzzy rough sets.
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References
Abu Arqub O (2017) Adaptation of reproducing kernel algorithm for solving fuzzy Fredholm-Volterra integrodifferential equations. Neural Comput Appl 28:1591–1610
Abu Arqub O, Singh J, Alhodaly M (2023) Adaptation of kernel functions-based approach with Atangana–Baleanu–Caputo distributed order derivative for solutions of fuzzy fractional Volterra and Fredholm integrodifferential equations, Mathematical Methods in the Applied Sciences 46,7:7807-7834
Abu Arqub O, Singh J, Maayah B et al (2023) Reproducing kernel approach for numerical solutions of fuzzy fractional initial value problems under the Mittag-Leffler kernel differential operator, Math Methods Appl Sci 46,7:7965–7986
Alshammari M, Al-Smadi M, Arqub OA et al (2020) Residual series representation algorithm for solving fuzzy duffing oscillator equations. Symmetry 12(4):572
Bao YL, Yang HL, She YH (2018) Using one axiom to characterize \(L\)-fuzzy rough approximation operators based on residuated lattices. Fuzzy Sets Syst 336:87–115
Belohlavek R (2012) Fuzzy relational systems: foundations and principles, Springer Science & Business Media
D’eer L, Verbiest N, Cornelis C, Godo L (2015) A comprehensive study of implicator-conjunctor-based and noise-tolerant fuzzy rough sets: definitions, properties and robustness analysis, Fuzzy Sets and Systems 275:1–38
El-Saady K, Hussein HS, Temraz AA (2022) A rough set model based on (\(L\), \(M\))-fuzzy generalized neighborhood systems: a constructive approach. Int J General Syst 51(5):441–473
Jiang HB, Hu BQ (2022) On \((O, G)\)-fuzzy rough sets based on overlap and grouping functions over complete lattices. Int J Approx Reason 144:18–50
Jiang HB, Zhan JM, Chen DG (2021) Covering-based variable precision \(L\)-fuzzy rough sets based on residuated lattices and corresponding applications. Int J Mach Learn Cybernet 12(8):2407–2429
Jin Q, Li LQ The axiomatic characterization on fuzzy variable precision rough sets based on residuated lattice, International Journal of General Systems, https://doi.org/10.1080/03081079.2023.2212849
Li W, Yang B, Qiao JS (2023) \((O, G)\)-granular variable precision fuzzy rough sets based on overlap and grouping functions. Comput Appl Math 42:107
Li W, Yang B, Qiao JS (2023) On three types of \(L\)-fuzzy \(\beta \)-covering-based rough sets. Fuzzy Sets Syst 461:108492
Liau CJ, Lin EB, Syau YR (2020) On consistent functions for neighborhood systems. Int J Approx Reason 121:39–58
Liu GL (2013) Using one axiom to characterize rough set and fuzzy rough set approximations. Inform Sci 223:285–296
Mi JS, Zhang WX (2004) An axiomatic characterization of a fuzzy generalization of rough sets. Inform Sci 160:235–249
Oh JM, Kim YC (2022) Various fuzzy connections and fuzzy concepts in complete co-residuated lattices. Int J Approx Reason 142:451–468
Pang B, Mi JS, Yao W (2019) \(L\)-fuzzy rough approximation operators via three new types of \(L\)-fuzzy relations. Soft Comput 23:11433–11446
Pawlak Z (1982) Rough sets. Int J Comput Inform Sci 11:341–356
Qiao JS, Hu BQ (2018) Granular variable precision \(L\)-fuzzy rough sets based on residuated lattices. Fuzzy Sets Syst 336:148–166
Radzikowska AM, Kerre EE (2005) Fuzzy rough sets based on Residuated lattices. Lecture Notes Comput Sci 3135:278–296
She YH, Wang GJ (2009) An axiomatic approach of fuzzy rough sets based on residuated lattices. Comput Math Appl 58:189–201
Shi ZQ, Xie SR, Li LQ (2023) Generalized fuzzy neighborhood system-based multigranulation variable precision fuzzy rough sets with double TOPSIS method to MADM. Inform Sci 643:119251
Sun Y, Pang B, Mi JS (2023) Axiomatic characterizations of \((O, G)\)-fuzzy rough approximation operators via overlap and grouping functions on a complete lattice. Int J General Syst 52(6):664–693
Syau YR, Lin EB (2014) Neighborhood systems and covering approximation spaces. Knowl-Based Syst 66:61–67
Syau YR, Lin EB, Liau CJ (2017) Neighborhood systems and variable precision generalized rough sets. Fundamenta Informaticae 153(3):271–290
Wang CY, Zhang XG, Wu YH (2020) New results on single axioms for \(L\)-fuzzy rough approximation operators. Fuzzy Sets Syst 380:131–149
Wei XW, Pang B, Mi JS (2021) Axiomatic characterizations of \(L\)-valued rough sets using a single axiom, Inform Sci 580:283–310
Wu WZ, Leung Y, Shao MW (2013) Generalized fuzzy rough approximation operators determined by fuzzy implicators. Int J Approx Reason 54:1388–1409
Wu WZ, Leung Y, Shao MW, Wang X (2019) Using single axioms to characterize \((S, T)\)-intuitionistic fuzzy rough approximation operators. Int J Mach Learn Cybernet 10(1):27–42
Wu WZ, Xu YH, Shao MW, Wang GY (2016) Axiomatic characterizations of \((S, T)\)-fuzzy rough approximation operators. Inform Sci 334–335:17–43
Xu YL, Zou DD, Li LQ, Yao BX (2023) \(L\)-fuzzy covering rough sets based on complete co-residuated lattice. Int J Mach Learn Cybernet 14(8):2815–2829
Yao YY (1998) Constructive and algebraic methods of the theory of rough sets. Inform Sci 109:21–47
Yao YY, Lin TY (1996) Generalization of rough sets using modal logic. Intell Autom Soft Comput 2(2):103–120
Yao YQ, Mi JS, Li ZJ (2014) A novel variable precision \((\Xi ,\sigma )\)-fuzzy rough set model based on fuzzy granules. Fuzzy Sets Syst 236:58–72
Zadeh LA (1965) Fuzzy sets. Inform Control 8(3):338–353
Zhang YL, Li JJ, Wu WZ (2010) On axiomatic characterizations of three pairs of covering based approximation operators. Inform Sci 180:274–287
Zhao FF, Shi FG (2021) \(L\)-fuzzy generalized neighborhood system operator-based \(L\)-fuzzy approximation operators. Int J General Syst 50(4):458–484
Zhao XR, Hu BQ (2015) Fuzzy variable precision rough sets based on residuated lattices. Int J General Syst 44:743–765
Ziarko W (1993) Variable precision rough set model. J Comput Syst Sci 46:39–59
Zou DD, Xu YL, Li LQ, Ma ZM (2023) Novel variable precision fuzzy rough sets and three-way decision model with three strategies. Inform Sci 629:222–248
Zou DD, Xu YL, Li LQ, Wu WZ (2023) A novel granular variable precision fuzzy rough set model and its application in fuzzy decision system. Soft Comput 27:8897–8918
Zhu W (2007) Generalized rough sets based on relations. Inform Sci 177(22):4997–5011
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The authors thank the editor and the reviewers for their valuable comments and suggestions.
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This work was supported by National Natural Science Foundation of China (No. 12171220), and Natural Science Foundation of Shandong Province (No. ZR2023MA079), and Discipline with Strong Characteristics of Liaocheng University—Intelligent Science and Technology under Grant 319462208.
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Jin, Q., Li, LQ. Several L-fuzzy variable precision rough sets and their axiomatic characterizations. Soft Comput 27, 16429–16448 (2023). https://doi.org/10.1007/s00500-023-09183-9
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DOI: https://doi.org/10.1007/s00500-023-09183-9