Skip to main content
Log in

Relative measure-based approaches for ranking single-valued neutrosophic values and their applications

  • Original Article
  • Published:
International Journal of Machine Learning and Cybernetics Aims and scope Submit manuscript

Abstract

During uncertain information processing on generalized fuzzy values, how to rank two single-valued neutrosophic values is an important and omnipresent issue in all kinds of intelligent decision problems solving. Although many orders have been proposed to compare any two single-valued neutrosophic values, some shortcomings may exist when they are utilized. Inspired by the Euclidean approach for ranking intuitionistic fuzzy values, we present two types of orders by using the notion of relative geometric distance and relative similarity degree, respectively. First, we present two relative distance-based and relative similarity-based measures to describe the favorable degree of the single-valued neutrosophic value by considering three distances and similarity degrees between a single-valued neutrosophic value and the ideal negative point, ideal positive point, and most uncertain point. Second, two orders over the set of all single-valued neutrosophic values and the corresponding ranking methods for single-valued neutrosophic sets are devised on the basis of the presented measures of an single-valued neutrosophic value, and their properties are discussed. Third, we extend the presented ranking method for single-valued neutrosophic values and single-valued neutrosophic sets by introducing human attitudes using different weights. Finally, we apply the presented methods to optimal alternative selection and group decision making and obtain the effective and reasonable results. The main thoughts of this study can be applied in various generalized fuzzy decision problem solving.

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

  1. Abdel-Basset M, Manogaran G, Mohamed M, Chilamkurti N (2018) Three-way decisions based on neutrosophic sets and AHP-QFD framework for supplier selection problem. Future Gener Comput Syst 89:19–30

    Article  Google Scholar 

  2. Atanassov KT (1986) Intuitionistic fuzzy sets. Fuzzy Sets Syst 20:87–96

    Article  MATH  Google Scholar 

  3. Atanassov KT, Gargov G (1989) Interval-valued intuitionistic fuzzy sets. Fuzzy Sets Syst 31:343–349

    Article  MathSciNet  MATH  Google Scholar 

  4. Basha SH, Tharwat A, Abdalla A, Hassanien AE (2019) Neutrosophic rule-based prediction system for toxicity effects assessment of biotransformed hepatic drugs. Expert Syst Appl 121:142–157

    Article  Google Scholar 

  5. Chen S, Tan J (1994) Handling multicriteria fuzzy decision-making problems based on vague set theory. Fuzzy Sets Syst 67:163–172

    Article  MathSciNet  MATH  Google Scholar 

  6. Deli I, Subas Y (2017) A ranking method of single valued neutrosophic numbers and its applications to multi-attribute decision making problems. Int J Mach Learn Cybern 8:1309–1322

    Article  Google Scholar 

  7. Gau WL, Buehrer DJ (1993) Vague sets. IEEE Trans Syst Man Cybern 23:610–614

    Article  MATH  Google Scholar 

  8. Han J, Yang C, Lim CC, Zhou X, Shi P, Gui W (2020) Power scheduling optimization under single-valued neutrosophic uncertainty. Neurocomputing 382:12–20

    Article  Google Scholar 

  9. Hong D, Choi C (2000) Multicriteria fuzzy decision-making problems based on vague set theory. Fuzzy Sets Syst 114:103–113

    Article  MATH  Google Scholar 

  10. Huang B, Liu J, Guo C, Li H, Feng G (2021) Relative-distance-based approaches for ranking intuitionistic fuzzy values. Artif Intell Rev 54:3089–3114

    Article  Google Scholar 

  11. Huang HL (2016) New distance measure of single-valued neutrosophic sets and its application. Int J Inlell Syst 31:1021–1032

    Article  Google Scholar 

  12. Jiao L, Yang HL, Li SG (2020) Three-way decision based on decision-theoretic rough sets with single-valued neutrosophic information. Int J Mach Learn Cybern 11:657–665

    Article  Google Scholar 

  13. Kandasamy I, Vasantha WB, Obbineni JM, Smarandache F (2020) Sentiment analysis of tweets using refined neutrosophic sets. Comput Ind 115:103180

    Article  Google Scholar 

  14. Karaaslan F, Hayat K (2018) Some new operations on single-valued neutrosophic matrices and their applications in multi-criteria group decision making. Appl Intell 48:4594–4614

    Article  Google Scholar 

  15. Liu P, Teng F (2018) Multiple attribute decision making method based on normal neutrosophic generalized weighted power averaging operator. Int J Mach Learn Cybern 9:281–293

    Article  Google Scholar 

  16. Liu P, Wang P, Liu J (2019) Normal neutrosophic frank aggregation operators and their application in multi-attribute group decision making. Int J Mach Learn Cybern 10:833–852

    Article  Google Scholar 

  17. Liu X, Dai J, Chen J, Wang C, Zhan J (2021) Measures of uncertainty based on Gaussian kernel for type-2 fuzzy information systems. Int J Fuz Syst 23:1163–1178

    Article  Google Scholar 

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

    Article  MathSciNet  MATH  Google Scholar 

  19. Mandal K, Basu K (2019) Vector aggregation operator and score function to solve multi-criteria decision making problem in neutrosophic environment. Int J Mach Learn Cybern 10:1373–1383

    Article  Google Scholar 

  20. Mendel JM, John RI, Liu FL (2006) Interval type-2 fuzzy logical systems made simple. IEEE Tran Fuzzy Syst 14(6):808–821

    Article  Google Scholar 

  21. Meng F, Wang N, Xu Y (2020) Triangular fuzzy neutrosophic preference relations and their application in enterprise resource planning software selection. Cogn Comput 12:261–295

    Article  Google Scholar 

  22. Peng JJ, Wang JQ, Wang J, Zhang HY, Chen XH (2016) Simplified neutrosophic sets and their applications in multi-criteria group decision-making problems. Int J Syst Sci 47:2342–2358

    Article  MATH  Google Scholar 

  23. 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

    Article  Google Scholar 

  24. Peng X, Dai J (2020) A bibliometric analysis of neutrosophic set: two decades review from 1998 to 2017. Artif Intell Rev 53:199–255

    Article  Google Scholar 

  25. Peng X, Smarandache F (2020) New multiparametric similarity measure for neutrosophic set with big data industry evaluation. Artif Intell Rev 53:3089–3125

    Article  Google Scholar 

  26. Pramanik S, Biswas P, Giri BC (2017) Hybrid vector similarity measures and their applications to multi-attribute decision making under neutrosophic environment. Neur Comput Appl 28:1163–1176

    Article  Google Scholar 

  27. Refaat R, El-Henawy IM (2019) Innovative method to evaluate quality management system audit results’ using single value neutrosophic number. Cogn Syst Res 57:197–206

    Article  Google Scholar 

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

    MATH  Google Scholar 

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

    Google Scholar 

  30. Turksen IB (1986) Interval valued fuzzy sets based on normal forms. Fuzzy Sets Syst 20:191–210

    Article  MathSciNet  MATH  Google Scholar 

  31. Wang H, Smarandache F, Zhang YQ, Sunderraman R (2010) Single valued neutrosophic sets. Multispace Multistruct 4:410–413

    MATH  Google Scholar 

  32. Wu H, Ye Y, Wei L, Pei L (2018) On entropy, similarity measure and cross-entropy of single-valued neutrosophic sets and their application in multi-attribute decision making. Soft Comput 22:7367–7376

    Article  Google Scholar 

  33. Xing Z, Xiong W, Liu H (2018) A Euclidean approach for ranking intuitionistic fuzzy values. IEEE Trans Fuzzy Syst 26:353–365

    Article  Google Scholar 

  34. Xu Z, Yager RR (2006) Some geometric aggregation operators based on intuitionistic fuzzy sets. Int J Gen Syst 35:417–433

    Article  MathSciNet  MATH  Google Scholar 

  35. Yang H, Zhang C, Guo Z, Liu Y, Liao X (2017) A hybrid model of single valued neutrosophic sets and rough sets: single valued neutrosophic rough set model. Soft Comput 21:6253–6267

    Article  MATH  Google Scholar 

  36. Ye J (2014) Clustering methods using distance-based similarity measures of single-valued neutrosophic sets. J Intell Syst 23:379–389

    Article  Google Scholar 

  37. 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 

  38. Ye J (2017) Simplified neutrosophic harmonic averaging projection-based method for multiple attribute decision-making problems. Int J Mach Learn Cybern 8:981–987

    Article  Google Scholar 

  39. Ye J, Du S (2019) Some distances, similarity and entropy measures for interval valued neutrosophic sets and their relationship. Int J Mach Learn Cybern 10:347–355

    Article  Google Scholar 

  40. Zadeh LA (1965) Fuzzy sets. Inf Control 8(3):338–353

    Article  MATH  Google Scholar 

  41. Zhang C, Li D, Kang X, Song D, Sangaiah AK, Broumi S (2020) Neutrosophic fusion of rough set theory: an overview. Comput Ind 115:103117

    Article  Google Scholar 

  42. Zhang C, Zhai Y, Li D, Mu Y (2016) Steam turbine fault diagnosis based on single-valued neutrosophic multigranulation rough sets over two universes. J Intell Fuzzy Syst 31:2829–2837

    Article  MATH  Google Scholar 

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

    Article  Google Scholar 

Download references

Acknowledgements

This work was supported by the Natural Science Foundation of the Jiangsu Higher Education Institutions of China (Grant no. 20KJA520006) and Postgraduate Research and Practice Innovation Program of Jiangsu Province (KYCX20_1681).

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Bing Huang or Chunxiang Guo.

Additional information

Publisher's Note

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

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Huang, B., Yang, X., Feng, G. et al. Relative measure-based approaches for ranking single-valued neutrosophic values and their applications. Int. J. Mach. Learn. & Cyber. 13, 1535–1552 (2022). https://doi.org/10.1007/s13042-021-01464-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13042-021-01464-9

Keywords

Navigation