Skip to main content
Log in

On hesitant neutrosophic rough set over two universes and its application

  • Published:
Artificial Intelligence Review Aims and scope Submit manuscript

Abstract

As a further generalization of the concepts of fuzzy set, intuitionistic fuzzy set, single valued neutrosophic refined set, hesitant fuzzy set, and dual hesitant fuzzy set, Ye (J Intell Syst 24(1):23–36, 2015) proposed the concept of hesitant neutrosophic sets (also called single valued neutrosophic hesitant fuzzy sets). Following the idea of hesitant neutrosophic sets as introduced by Ye, in this paper, the model of hesitant neutrosophic rough sets is proposed, then the join semi-lattice structure of lower and upper hesitant neutrosophic rough approximation operators over two universes is given. In addition, an algorithm to handle decision making problem in medical diagnosis based on hesitant neutrosophic rough sets over two universes is provided. Finally, a numerical example is employed to demonstrate the validness of the proposed hesitant neutrosophic rough sets.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Atanassov K (1986) Intuitionistic fuzzy sets. Fuzzy Sets Syst 20(1):87–96

    MATH  Google Scholar 

  • Bao YL, Yang HL (2017) On single valued neutrosophic refined rough set model and its applition. J Intell Fuzzy Syst 33(2):1235–1248

    Article  MathSciNet  MATH  Google Scholar 

  • Biswas P, Pramanik S, Giri BC (2016) GRA method of multiple attribute decision making with single valued neutrosophic hesitant fuzzy set information. In: Smarandache F, Pramanik S (eds) New trends in neutrosophic theory and applications. Pons Editions, Brussels, pp 55–63

    Google Scholar 

  • Bo CX, Zhang XH, Shao ST, Smarandache F (2018) Multi-granulation neutrosophic rough sets on a single domain and dual domains with applications. Symmetry. https://doi.org/10.3390/sym10070296

    Article  Google Scholar 

  • Broumi S, Smarandache F (2014) Rough neutrosophic sets. Ital J Pure Appl Math 32:493–502

    MathSciNet  MATH  Google Scholar 

  • Guo Y, Cheng HD (2009) A new neutrosophic approach to image segmentation. Pattern Recognit 42:587–595

    Article  MATH  Google Scholar 

  • Guo Y, Sengur A (2015) NCM: neutrosophic c-means clustering algorithm. Pattern Recognit 48(8):2710–2724

    Article  Google Scholar 

  • Khan Q, Mahmood T, Ye J (2017) Multiple attribute decision-making method under hesitant single valued neutrosophic uncertain linguistic environment. J Inequal Spec Funct 8(2):17

    MathSciNet  Google Scholar 

  • Li ZW, Cui RC (2015a) \(T\)-similarity of fuzzy relations and related algebraic structures. Fuzzy Sets Syst 275:130–143

    MathSciNet  MATH  Google Scholar 

  • Li ZW, Cui RC (2015b) Similarity of fuzzy relations based on fuzzy topologies induced by fuzzy rough approximation operators. Inf Sci 305:219–233

    Article  MathSciNet  MATH  Google Scholar 

  • Li X, Zhang XH (2018) Single-valued neutrosophic hesitant fuzzy Choquet aggregation operators for multi-attribute decision making. Symmetry. https://doi.org/10.3390/sym10020050

    Article  MATH  Google Scholar 

  • Li ZW, Liu XF, Zhang GQ, NiX Xie, Wang SC (2017) A multi-granulation decision-theoretic rough set method for distributed fc-decision information systems: an application in medical diagnosis. Appl Soft Comput 56:233–244

    Article  Google Scholar 

  • Liu PD, Teng F (2017) Some interval-valued Neutrosophic hesitant fuzzy uncertain linguistic Bonferroni mean aggregation operators and their application in multiple attribute decision making. Int J Uncertain Quantif 7(6):525–572

    Article  Google Scholar 

  • Liu PD, Zhang LL (2017) An extended multiple criteria decision-making method based on neutrosophic hesitant fuzzy information. J Intell Fuzzy Syst 32(6):4403–4413

    Article  MATH  Google Scholar 

  • Mahmood T, Ye J, Khan Q (2016) Vector similarity measures for simplified neutrosophic hesitant fuzzy set and their applications. J Inequal Spec Funct 7(4):176–194

    Google Scholar 

  • Majumdar P, Samant SK (2014) On similarity and entropy of neutrosophic sets. J Intell Fuzzy Syst 26(3):1245–1252

    Article  MathSciNet  MATH  Google Scholar 

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

    Article  MATH  Google Scholar 

  • Şahin R, Küçük A (2015) Subsethood measure for single valued neutrosophic sets. J Intell Fuzzy Syst 29(2):525–530

    Article  MATH  Google Scholar 

  • Şahin R, Liu PD (2016) Correlation coefficient of single-valued neutrosophic hesitant fuzzy sets and its applications in decision making. Neural Comput Appl. https://doi.org/10.1007/s00521-015-2163-x

    Article  Google Scholar 

  • Salama AA, Broumi S (2014) Roughness of neutrosophic sets. Elixir Appl Math 74:26833–26837

    Google Scholar 

  • Smarandache F (1998) Neutrosophy: neutrosophic probability, set, and logic. American Research Press, Rehoboth

    MATH  Google Scholar 

  • Smarandache F (1999) A unifying field in logics. neutrosophy: neutrosophic probability, set and logic. American Research Press, Rehoboth

    MATH  Google Scholar 

  • Smarandache F (2002) A unifying field in logics: neutrosophic logic. Int J Mult Valued Log 8(3): 385–438, ISSN: 1023–6627

  • Torra V (2010) Hesitant fuzzy sets. Int J Intell Syst 25:529–539

    MATH  Google Scholar 

  • Torra V, Narukawa Y (2009) on hesitant fuzzy sets and decision. In: The 18th IEEE international conference on fuzzy systems. Jeju Island, pp 1378–1382

  • Xia MM, Xu ZS (2011) Hesitant fuzzy information aggregation in decision making. Int J Approx Reason 52:395–407

    Article  MathSciNet  MATH  Google Scholar 

  • Xu ZS, Xia MM (2011) Distance and similarity measures for hesitant fuzy sets. inform. Sciences 181:2128–2138

    MATH  Google Scholar 

  • Yang HL, Guo ZL, She YH, Liao XW (2016) On single valued neutrosophic relations. J Intell Fuzzy Syst 30:1045–1056

    Article  MATH  Google Scholar 

  • 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(21):6253–6267

    Article  MATH  Google Scholar 

  • Ye J (2013) Multicriteria decision-making method using the correlation coefficient under single-valued neutrosophic environment. Int J Gen Syst 42(4):386–394

    Article  MathSciNet  MATH  Google Scholar 

  • Ye J (2014) Improved correlation coefficients of single valued neutrosophic sets and interval neutrosophic sets for multiple attribute decision making. J Intell Fuzzy Syst 27:2453–2462

    Article  MATH  Google Scholar 

  • Ye J (2015) Multiple-attribute decision-making method using the under a single-valued neutrosophic hesitant fuzzy environment. J Intell Syst 24(1):23–36

    Article  Google Scholar 

  • Ye J (2016) Correlation coefficients of interval neutrosophic hesitant fuzzy sets and its application in a multiple attribute decision making method. Informatica 27(1):179–202

    Article  MATH  Google Scholar 

  • Ye J (2018) Multiple-attribute decision-making method using similarity measures of single-valued neutrosophic hesitant fuzzy sets based on least common multiple cardinality. J Intell Fuzzy Syst 34(6):4203–4211

    Article  Google Scholar 

  • Ye S, Ye J (2014) Dice similarity measure between single valued neutrosophic multisets and its applcation in medical diagnosis. Neutrosophic Sets Syst 6:48–53

    Google Scholar 

  • Zhang C, Li DY, Mu YM, Song D (2016) An interval-valued hesitant fuzzy multigranulation rough set over two universes model for steam turbine fault diagnosis. Appl Math Modell. https://doi.org/10.1016/j.apm.2016.10.048

    Article  MATH  Google Scholar 

  • Zhang HD, Shu L, Liao SL (2017a) Hesitant fuzzy rough set over two universes and its application in decision making. Soft Comput 21(7):1803–1816

    Article  MATH  Google Scholar 

  • Zhang XH, Smarandache F, Liang XL (2017b) Neutrosophic duplet semi-group and cancellable neutrosophic triplet groups. Symmetry. https://doi.org/10.3390/sym9110275

    Article  Google Scholar 

  • Zhang XH, Bo CX, Smarandache F, Dai JH (2018a) New inclusion relation of neutrosophic sets with applications and related lattice structure. Int J Mach Learn Cybern 9:1753–1763

    Article  Google Scholar 

  • Zhang XH, Bo CX, Smarandache F, Park C (2018b) New operations of Totally dependent-neutrosophic sets and totally dependent-neutrosophic soft sets. Symmetry. https://doi.org/10.3390/sym10060187

    Article  Google Scholar 

  • Zhao H, Zhang HY (2018a) A result on single valued neutrosophic refined rough approximation operators. J Intell Fuzzy Syst 35:3139–3146

    Article  Google Scholar 

  • Zhao H, Zhang HY (2018b) Some results on multigranulation neutrosophic rough sets on a single domain. Symmetry. https://doi.org/10.3390/sym10090417

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Hu Zhao.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

The work is partly supported by the National Natural Science Foundation of China (Grant Nos. 11771263, 11671007), the Applied Basic Research Program Funded by Qinghai Province (Program No. 2019-ZJ-7078), the Scientific Research Program Funded by Shaanxi Provincial Education Department (Program No. 18JK0360), and the Doctoral Scientific Research Foundation of Xi’an Polytechnic University (Grant No. BS1426).

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhao, H., Zhang, HY. On hesitant neutrosophic rough set over two universes and its application. Artif Intell Rev 53, 4387–4406 (2020). https://doi.org/10.1007/s10462-019-09795-4

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10462-019-09795-4

Keywords

Navigation