Abstract
This paper presents a general framework for the study of \(({\mathcal {I}}, {\mathcal {N}})\)-single valued neutrosophic rough sets from constructive and axiomatic perspectives. In the constructive approach, a pair of single valued neutrosophic rough approximation operators based on single valued neutrosophic implicator \({\mathcal {I}}\) and single valued neutrosophic norm \({\mathcal {N}}\) is first proposed. Moreover, some basic properties of \(({\mathcal {I}},{\mathcal {N}})\)-single valued neutrosophic rough approximation operators are explored. In addition, connections between single valued neutrosophic relations and \((\mathcal {I},{\mathcal {N}})\)-single valued neutrosophic rough approximation operators are systematically discussed. In the axiomatic approach, axiomatic characterization of \(({\mathcal {I}},{\mathcal {N}})\)-single valued neutrosophic approximation operators is studied. Specifically, different axiom sets characterizing the intrinsic properties of \((\mathcal {I},{\mathcal {N}})\)-single valued neutrosophic rough approximation operators associated with diverse single valued neutrosophic relations are investigated in detail.
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References
Alkhazaleh S (2015) More on neutrosophic norms and conorms. Neutrosophic Sets Syst 9:23–30
Broumi S, Smarandache F (2015) Interval neutrosophic rough set. Neutrosophic Sets Syst 7:23–31
Broumi S, Smarandache F, Dhar M (2010) Rough neutrosophic sets. Ital J Pure Appl Math 32(32):493–502
Bao YL, Yang HL (2017) On single valued neutrosophic refined rough set model and its application. J Intell Fuzzy Syst 33:1235–1248
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
Cornelis C, Cock MD, Kerre EE (2003) Intuitionistic fuzzy rough sets: at the crossroads of imperfect knowledge. Expert Syst 20(5):260–270
Cornelis C, Deschrijver G (2001) The compositional rule of inference in an intuitionistic fuzzy logic setting. In: Striegnitz K (ed) Proceedings ESSLLI 2001 student session, p 83–94
Cornelis C, Deschrijver G, Kerre EE (2004) Implication in intuitionistic fuzzy and interval-valued fuzzy set theory: construction, classification, application. Int J Approx Reason 35(1):55–95
Deschrijver G, Cornelis C, Kerre EE (2004) On the representation of intuitionistic fuzzy t-norms and t-conorms. IEEE Trans Fuzzy Syst 12(1):45–61
Dubois D, Prade H (1990) Rough fuzzy sets and fuzzy rough sets. Int J Gen Syst 17(2–3):191–209
Guo YH, Cheng HD (2009) New neutrosophic approach to image segmentation. Pattern Recognit 42(5):587–595
Guo YH, Sengur A (2015) NCM: neutrosophic c-means clustering algorithm. Pattern Recognit 48(8):2710–2724
Li LQ, Jin Q, Hu K, Zhao FF (2017) The axiomatic characterizations on \(L\)-fuzzy covering-based approximation operators. Int J Gen Syst 46(2):1–22
Li TJ, Yang XP (2014) An axiomatic characterization of probabilistic rough sets. Int J Gen Syst Approx Reason 55(1):130–141
Liu PD, Wang YM (2016) Interval neutrosophic prioritized OWA operator and its application to multiple attribute decision making. J Syst Sci Complex 29(3):681–697
Liu GL (2013) Using one axiom to characterize rough set and fuzzy rough set approximations. Inf Sci 223:285–296
Ma X, Zhan J, Ali MI, Mehmood N (2018) A survey of decision making methods based on two classes of hybrid soft set models. Artif Intell Rev 49(4):511–529
Mi JS, Zhang WX (2004) An axiomatic characterization of a fuzzy generalization of rough sets. Inf Sci 160(1–4):235–249
Pawlak Z (1982) Rough sets. Int J Comput Inf Sci 11:341–356
Pawlak Z (1991) Rough sets: theoretical aspects of reasoning about data. Kluwer Academic Publishers, Boston
Peng JJ, Wang JQ, Zhang HY, Chen XH (2014) An outranking approach for multi-criteria decision-making problems with simplified neutrosophic sets. Appl Soft Comput 25:336–346
Rivieccio U (2008) Neutrosophic logics: prospects and problems. Fuzzy Sets Syst 159(14):1860–1868
Salama AA, Broumi S (2014) Roughness of neutrosophic sets. Elixir Appl Math 74:26833–26837
Smarandache F (1998) Neutrosophy: neutrosophic probability, set, and logic. American Research Press, Rehoboth
Smarandache F (1999) A unifying field in logics. Neutrosophy: neutrosophic probability, set and logic. American Research Press, Rehoboth
Smarandache F (2013) \(n\)-valued refined neutrosophic logic and its applications in physics. Prog Phys 4:143–146
Smarandache F (2010) N-norm and N-conorm in neutrosophic logic and set, and the neutrosophic topologies. Multispace Multistructrue 4:436–446
Smarandache F (2015) Symbolic neutrosophic logic. Europa Nova, Bruxelles
Smets P, Magrez P (1987) Implication in fuzzy logic. Int J Approx Reason 1(4):327–347
Wang HB, Smarandache F, Sunderraman R (2010) Single valued neutrosophic sets. Multispace Multistruct 4:410–413
Wang CY (2018) Single axioms for lower fuzzy rough approximation operators determined by fuzzy implications. Fuzzy Sets Syst 336:116–147
Wu WZ, Leung Y, Shao MW (2013) Generalized fuzzy rough approximation operators determined by fuzzy implicators. Int J Approx Reason 54(9):1388–1409
Wu WZ, Li TJ, Gu SM (2015) Using one axiom to characterize fuzzy rough approximation operators determined by a fuzzy implication operator. Fundam Inf 142:87–104
Wu WZ, Xu YH, Shao MW, Wang GY (2016) Axiomatic characterizations of \((S, T)\)-fuzzy rough approximation operators. Inf Sci 334:17–43
Yang HL, Guo ZL, She YH, Liao XW (2014) On single valued neutrosophic relations. J Intell Fuzzy Syst 30(2):1045–1056
Yang HL, Zhang CL, Guo ZL, Liu YL, Liao XW (2017) A hybrid model of single valued neutrosophic sets and rough sets: single valued neutrosophic rough set model. Soft Comput 21:6253–6267
Yang HL, Bao YL (2018) Generalized interval neutrosophic rough sets and its application in multi-attribute decision making. Filomat 32(1):11–33
Yao YY (1998) Constructive and algebraic methods of the theory of rough sets. Inf Sci 109(1–4):21–47
Yao YY (1998) On generalizing Pawlak approximation operators, In: International conference on rough sets and current trends in computing, Springer, Berlin, pp 298–307
Ye J (2014) A multicriteria decision-making method using aggregation operators for simplified neutrosophic sets. J Intell Fuzzy Syst 26(5):2459–2466
Ye J (2014) Single valued neutrosophic cross-entropy for multicriteria decision making problems. Appl Math Modell 38(3):1170–1175
Zhang ZM (2010) An interval-valued rough intuitionistic fuzzy set model. Int J Gen Syst 39(2):135–164
Zhan J, Xu W (2018) Two types of coverings based multigranulation rough fuzzy sets and applications to decision making. Artif Intell Rev. https://doi.org/10.1007/s10462-018-9649-8
Zhan J, Wang Q (2018) Certain types of soft coverings based rough sets with applications. Int J Mach Learn Cybern https://doi.org/10.1007/s13042-018-0785-x
Zhang L, Zhan J, Alcantud JCR (2018) Novel classes of fuzzy soft-coverings-based fuzzy rough sets with applications to multi-criteria fuzzy group decision making, Soft Comput. https://doi.org/10.1007/s00500-018-3470-9
Zhang L, Zhan J (2018) Fuzzy soft -covering based fuzzy rough sets and corresponding decision-making applications. Int J Mach Learn Cybern https://doi.org/10.1007/s13042-018-0828-3
Zhang Q, Wang J, Wang G, Yu H (2015) The approximation set of a vague set in rough approximation space. Inf Sci 300:1–19
Zhang Q, Xu K, Wang G (2016) Fuzzy equivalence relation and its multi-granulation spaces. Inf Sci 346–347:44–57
Zhou L, Wu WZ, Zhang WX (2009) On characterization of intuitionistic fuzzy rough sets based on intuitionistic fuzzy implicators. Inf Sci 179(7):883–898
Zhou NL, Hu BQ (2016) Axiomatic approaches to rough approximation operators on complete completely distributive lattices. Inf Sci 348:227–242
Zhu W (2009) Relationship among basic concepts in covering-based rough sets. Inf Sci 179(14):2478–2486
Acknowledgements
This work is partly supported by the National Natural Science Foundation of China (Nos. 61473181 and 11771263) and the Fundamental Research Funds for the Central Universities (Nos. GK201702008 and 2016TS034).
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Bao, YL., Yang, HL. & Li, SG. On characterization of \((\mathcal {I},{\mathcal {N}})\)-single valued neutrosophic rough approximation operators. Soft Comput 23, 6065–6084 (2019). https://doi.org/10.1007/s00500-018-3613-z
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DOI: https://doi.org/10.1007/s00500-018-3613-z