[go: up one dir, main page]
More Web Proxy on the site http://driver.im/ Skip to main content
Log in

Roughness of linear Diophantine fuzzy sets by intuitionistic fuzzy relations over dual universes with decision-making applications

  • Published:
Computational and Applied Mathematics Aims and scope Submit manuscript

Abstract

Rough sets (RSs) and fuzzy sets (FSs) are designed to tackle the uncertainty in the data. By taking into account the control or reference parameters, the linear Diophantine fuzzy set (LD-FS) is a novel approach to decision making (DM), broadens the previously dominant theories of the intuitionistic fuzzy set (IFS), Pythagorean fuzzy set (PyFS), and q-rung orthopair fuzzy set (q-ROFS), and allows for a more flexible representation of uncertain data. A promising avenue for RS theory is to investigate RSs within the context of LD-FS, where LD-FSs are approximated by an intuitionistic fuzzy relation (IFR). The major goal of this article is to create a novel method of roughness for LD-FSs employing an IFR over dual universes. The notions of lower and upper approximations of an LD-FS are established by using an IFR, and some axiomatic systems are carefully investigated in detail. Moreover, a link between LD-FRSs and linear Diophantine fuzzy topology (LDF-topology) has been established. Eventually, based on lower and upper approximations of an LD-FS, several similarity relations are investigated. Meanwhile, we apply the recommended model of LD-FRSs over dual universes for solving the DM problem. Furthermore, a real-life case study is given to demonstrate the practicality and feasibility of our designed approach. Finally, we conduct a detailed comparative analysis with certain existing methods to explore the effectiveness and superiority of the established technique.

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

Access this article

Subscribe and save

Springer+ Basic
£29.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (United Kingdom)

Instant access to the full article PDF.

Algorithm 1
Fig. 1
Fig. 2

Similar content being viewed by others

Data availability

Not applicable.

References

  • Ali MI (2018) Another view on q-rung orthopair fuzzy sets. Int J Intell Syst 33(11):2139–2153

    Google Scholar 

  • Ali J, Bashir Z, Rashid T (2021) Weighted interval-valued dual-hesitant fuzzy sets and its application in teaching quality assessment. Soft Comput 25:3503–3530

    Google Scholar 

  • Ali Z, Mahmood T, Santos-García G (2021) Heronian mean operators based on novel complex linear Diophantine uncertain linguistic variables and their applications in multi-attribute decision making. Mathematics 9(21):2730

    Google Scholar 

  • Almagrabi AO, Abdullah S, Shams M (2021) A new approach to q-linear Diophantine fuzzy emergency decision support system for COVID19. J Ambient Intell Humaniz Comput. https://doi.org/10.1007/s12652-021-03130-y

    Article  Google Scholar 

  • Alnoor A, Zaidan AA, Qahtan S, Alsattar HA, Mohammed RT, Khaw KW, Albahri AS (2022) Toward a sustainable transportation industry: oil company benchmarking based on the extension of linear Diophantine fuzzy rough sets and multicriteria decision-making methods. IEEE Trans Fuzzy Syst 31(2):449–459

    Google Scholar 

  • Al-shami TM (2022) Topological approach to generate new rough set models. Complex Intell Syst 8(5):4101–4113

    Google Scholar 

  • Atanassov KT (1984) Intuitionistic Fuzzy Relations. In: Antonov L (ed) III International School Automation and Scientiï Instrumentation. Varna, pp 56–57

  • Atanssov KT (1986) Intuintionistic fuzzy sets. Fuzzy Sets Syst 20:87–96

    Google Scholar 

  • Atanssov KT (1989) More on intuintionistic fuzzy sets. Fuzzy Sets Syst 33:37–45

    Google Scholar 

  • Ayub S, Shabir M, Riaz M, Aslam M, Chinram R (2021) Linear Diophantine fuzzy relations and their algebraic properties with decision making. Symmetry 13:945. https://doi.org/10.3390/sym13060945

    Article  Google Scholar 

  • Ayub S, Shabir M, Riaz M, Karaslan F, Marinkovic D, Vranjes D (2022a) Linear Diophantine fuzzy rough sets on paired universes with multi-stage decision analysis. Axioms 11(686):1–18. https://doi.org/10.3390/axioms11120686

    Article  Google Scholar 

  • Ayub S, Shabir M, Riaz M, Mahmood W, Bozanic D, Marinkovic D (2022b) Linear Diophantine fuzzy rough sets: a new rough set approach with decision making. Symmetry 14:525. https://doi.org/10.3390/sym14030525

    Article  Google Scholar 

  • Ayub S, Mahmood W, Shabir M, Koam ANA, Gul R (2022c) A study on soft multi-granulation rough sets and their applications. IEEE Access 10:115541–115554

    Google Scholar 

  • Ayub S, Shabir M, Gul R (2023) Another approach to Linear Diophantine fuzzy rough sets on two universes and its application towards decision-making problem. Phys Scripta 98(10):105240

    Google Scholar 

  • Bashir Z, Bashir Y, Rashid T, Ali J, Gao W (2019) A novel multi-attribute group decision-making approach in the framework of proportional dual hesitant fuzzy sets. Appl Sci 9(6):1232

    Google Scholar 

  • Bashir Z, Mahnaz S, Abbas Malik MG (2021) Conflict resolution using game theory and rough sets. Int J Intell Syst 36(1):237–259

    Google Scholar 

  • Bellman RE, Zadeh LA (1970) Decision-making in fuzzy environment. Manag Sci 4(17):141–164

    MathSciNet  Google Scholar 

  • Bilal MA, Shabir M (2021) Approximations of Pythagorean fuzzy sets over dual universes by soft binary relations. J Intell Fuzzy Syst 41:2495–2511

    Google Scholar 

  • Bilal MA, Shbair M, Al-Kenani Ahmad N (2021) Rough q-rung orthopair fuzzy sets and their applications in decision-making. Symmetry 13:1–22

    Google Scholar 

  • Boixder D, Jacas J, Recasens J (2000) Upper and lower approximations of fuzzy sets. Int J Gen Syst 29:555–568

    MathSciNet  Google Scholar 

  • Boran FE, Geniç S, Kurt M, Akay D (2009) A multi-criteria intuitionistic fuzzy group decision making for supplier selection with TOPSIS method. Expert Syst Appl 36:11363–11368

    Google Scholar 

  • Burillo P, Bustince H (1995) Intuitionistic fuzzy relations (Part I). Mathw Soft Comput 2(1):5–38

    Google Scholar 

  • Burillo P, Bustince H (1995) Intuitionistic fuzzy relations (Part II) Effect of Atanassov’s operators on the properties of the intuitionistic fuzzy relations. Mathw Soft Comput 2(2):117–148

    Google Scholar 

  • Bustince H (2000) Construction of intuitionistic fuzzy relations with predetermined properties. Fuzzy Sets Syst 109:379–403

    MathSciNet  Google Scholar 

  • Chang CL (1968) Fuzzy topological spaces. J Math Anal Appl 24:182–189

    MathSciNet  Google Scholar 

  • Coker D (1997) An introduction of intuitionistic fuzzy topological spaces. Fuzzy Sets Syst 88:81–89

    MathSciNet  Google Scholar 

  • Cornelis C, Deschrijver G, Kerre EE (2004) Implication in intuintionistic fuzzy and interval-valued fuzzy set theory: Construction, classification, application. Int J Approx Reason 35(1):55–95

    Google Scholar 

  • Davvaz B (2008) A short note on algebraic \(T-\)rough sets. Inf Sci 178:3247–3252

    MathSciNet  Google Scholar 

  • Deschrijver G, Kerre EE (2003) On the composition of intuitionistic fuzzy relations. Fuzzy Sets Syst 136:333–361

    MathSciNet  Google Scholar 

  • Dubois D, Prade H (1990) Fuzzy rough sets and rough fuzzy sets. Int J Gen Syst 17:191–209

    Google Scholar 

  • Dubois D, Prade H (2012) Gradualness, uncertainty and bipolarity: making sense of fuzzy sets. Fuzzy Sets Syst 192:3–24

    MathSciNet  Google Scholar 

  • El-Bably MK, Al-Shami TM (2021) Different kinds of generalized rough sets based on neighborhoods with a medical application. Int J Biomath 14(08):2150086

    MathSciNet  Google Scholar 

  • Gul R, Shabir M (2020) Roughness of a set by \((\alpha ,\beta )-\)indiscernibility of Bipolar fuzzy relation. Comput Appl Math 39(160):1–22. https://doi.org/10.1007/s40314-020-01174-y

    Article  MathSciNet  Google Scholar 

  • Iampan A, Garcia GS, Riaz M, Afrid HMA, Chinram R (2021) Linear Diophanine fuzzy Einstien aggregation operators for multi-criteria decision-making problems. J Math (Hindawi) 2021:1–31

    Google Scholar 

  • Ibrahim HZ, Al-shami TM, Mhemdi A (2023) Applications of \(n^{th}\) power root fuzzy sets in multicriteria decision making. J Math 2023:14

    Google Scholar 

  • Jäkel J, Mikut R, Bretthauer G (2004) Fuzzy control systems. In: Institute of Applied Computer Science, Forschungszentrum Karlsruhe GmbH, Germany, pp 1–31

  • Jana C, Pal M (2023) Interval-valued picture fuzzy uncertain linguistic dombi operators and their application in industrial fund selection. J Ind Intell 1(2):110–124

    Google Scholar 

  • Kamacı H (2021) Linear Diophantine fuzzy algebraic structures. J Ambient Intell Humaniz Comput 12(11):10353–10373. https://doi.org/10.1007/s12652-020-02826-x

    Article  Google Scholar 

  • Kamacı H (2022) Complex linear Diophantine fuzzy sets and their cosine similarity measures with applications. Complex Intell Syst 8(2):1281–1305

    MathSciNet  Google Scholar 

  • Khan AA, Wang L (2023) Generalized and group-generalized parameter based fermatean fuzzy aggregation operators with application to decision-making. Int J Knowl Innov Stud 1:10–29

    Google Scholar 

  • Kim E, Park M, Ji S, Park M (1997) A new approach to fuzzy modeling. IEEE Trans Fuzzy Syst 5(3):328–337

    Google Scholar 

  • Kortelainen J (1994) On relationship between modified sets, topological spaces and rough sets. Fuzzy Sets Syst 61:91–95

    MathSciNet  Google Scholar 

  • Kumar S, Gangwal C (2021) A study of fuzzy relation and its application in medical diagnosis. Asian Res J Math 17(4):6–11

    Google Scholar 

  • Kupongsak S, Tan J (2006) Application of fuzzy set and neural network techniques in determining food process control set points. Fuzzy Sets Syst 157(9):1169–1178

    MathSciNet  Google Scholar 

  • Lashin EF, Kozae AM, khadra AAA, Medhat T (2005) Rough set theory for topological spaces. Int J Approx Reason 40:35–43

    MathSciNet  Google Scholar 

  • Li TJ, Zhang WX (2008) Rough fuzzy approximations on two universes of discourse. Inf Sci 178(3):892–906

    MathSciNet  Google Scholar 

  • Liu P, Wang P (2018) Some q-rung orthopair fuzzy aggregation operators and their applications to multi-attribute DM. Int J Intell Syst 33:259–280

    Google Scholar 

  • Liu C, Miao D, Zhang N (2012) Graded rough set model based on two universes and its properties. Knowl-Based Syst 33:65–72

    Google Scholar 

  • Mahmood T, Ali Z, Aslam M, Chinram R (2021) Generalized Hamacher aggregation operators based on linear Diophantine uncertain linguistic setting and their applications in decision-making problems. IEEE Access 9:126748–126764

    Google Scholar 

  • Ming HC (1985) Fuzzy topological spaces. J Math Anal Appl 110:141–178

    MathSciNet  Google Scholar 

  • Mohammad MMS, Abdullah S, Al-Shomrani MM (2022) Some linear diophantine fuzzy similarity measures and their application in decision making problem. IEEE Syst Man Cybern Soc Sect 10:29859–29877

    Google Scholar 

  • Molodtsov D (1999) Soft set theory-first results. Comput Math Appl 37:19–31

    MathSciNet  Google Scholar 

  • Murali V (1989) Fuzzy equivalence relations. Fuzzy Sets Syst 30:155–163

    MathSciNet  Google Scholar 

  • Panpho P, Yiarayong P (2023) (p, q)-Rung linear Diophantine fuzzy sets and their application in decision-making. Comput Appl Math 42(8):324

    MathSciNet  Google Scholar 

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

    Google Scholar 

  • Pei D, Xu ZB (2004) Rough set models on two universes. Int J Gen Syst 33(5):569–581

    MathSciNet  Google Scholar 

  • Peng X (2019) New Similarity measure and distance measure for Pythagorean fuzzy set. Complex Intell Syst 5:101–111

    Google Scholar 

  • Qin KY, Pei Z (2005) On topological properties of fuzzy rough sets. Fuzzy Sets Syst 151:601–613

    MathSciNet  Google Scholar 

  • Riaz M, Farid HMA (2023) Enhancing green supply chain efficiency through linear Diophantine fuzzy soft-max aggregation operators. J Ind Intell 1(1):8–29

    Google Scholar 

  • Riaz M, Hashmi MR (2019) Linear Diophantine fuzzy set and its applications towards multi-attribute decision-making problems. J Intell Fuzzy Syst 37:5417–5439

    Google Scholar 

  • Riaz M, Davvaz B, Firdous A, Fakhar A (2019) Novel concepts of soft rough set topology with applications. J Intell Fuzzy Syst 36(4):3579–3590

    Google Scholar 

  • Riaz M, Hashmi MR, Kulsoom H, Pamucar D, Chu YM (2020) Linear Diophantine fuzzy soft rough sets for the selection of sustainable material handling equipment. Symmetry 12:1–39

    Google Scholar 

  • Riaz M, Farid HMA, Karaaslan F (2022) Linear Diophantine fuzzy aggregation operators with multi-criteria decision-making. J Comput Cogn Eng

  • Samanta SK, Mondal TK (2001) Intuitionistic fuzzy rough sets and rough intuitionistic fuzzy sets. J Fuzzy Math 9:561–582

    MathSciNet  Google Scholar 

  • Schwartz DG, Klir GJ, Lewis HW, Ezawa Y (1994) Applications of fuzzy sets in approximate reasoning. Proc IEEE 82(4):482–498

    Google Scholar 

  • Shabir M, Shaheen T (2016) A new methodology for fuzzification of rough sets based on \(\alpha -\)indiscernibility. Fuzzy Sets Syst 16:1–19

    MathSciNet  Google Scholar 

  • Shaheen T, Ali MI, Toor H (2021) Why do we need q-rung orhopair fuzzy sets? Some evidence established via mass assignment. Int J Intell Syst 36:5493–5505

    Google Scholar 

  • She Y, He X, Shi H, Qian Y (2017) A multiple-valued logic approach for multigranulation rough set model. Int J Approx Reason 82:270–284

    MathSciNet  Google Scholar 

  • Skowron A (1988) On topology in information systems. Bull Polish Acad Sci Math 36(7–8):477–479

    MathSciNet  Google Scholar 

  • Sun BZ, Ma WM (2011) Fuzzy rough set model on two different universes and its applications. Appl Math Model 35:1798–1809

    MathSciNet  Google Scholar 

  • Sun B, Ma W, Liu Q (2012) An approach to decision making based on intuitionistic fuzzy rough sets over two universes. J Oper Res Soc 64:1–11

    Google Scholar 

  • Sun G, Guan X, Yi X, Zhou Z (2018) Grey relational analysis between hesitant fuzzy sets with applications to pattern recognition. Expert Syst Appl 92:521–532

    Google Scholar 

  • Tang W, Wu J, Zheng D (2014) On fuzzy rough sets and their toplogical structuers. Hindawi Publ Coporat Math Probl Eng 2014:1–17 (ID: 546372)

    Google Scholar 

  • Tükraslan E, Ünver M, Olgun M (2021) q-rung orthopair fuzzy topologial spaces. Lobachevskii J Math 42:470–478

    MathSciNet  Google Scholar 

  • Wang XZ, Ruan D, Kerre EE (2009) Mathematics of fuzziness-basic issues. Stud Fuzzin Soft Comput 245:1–227

    MathSciNet  Google Scholar 

  • Wiweger A (1989) On topological rough sets. Bull Polish Acad Sci Math 37(1–6):89–93

    MathSciNet  Google Scholar 

  • Wu W, Zhou L (2011) On intuitionistic fuzzy topologies based on intuitionistic fuzzy reflexive and transitive relations. Soft Comput 15:1183–1194

    Google Scholar 

  • Yager RP (2013) Pythagorean fuzzy subsets. In: Proceedings of the IFSA World Congress and NAFIPS Anual Meeting, Edmonton, AB Canada, pp 57–61

  • Yager RP (2014) Pythagorean membership grades in multi-criteria decision marking. IEEE Trans Fuzzy Syst 22:958–965

    Google Scholar 

  • Yager RP (2017) Generalized orthopair fuzzy sets. IEEE Trans Fuzzy Syst 25:1222–1230

    Google Scholar 

  • Yan R, Zheng J, Liu J, Zhai Y (2010) Research on the model of rough set over dual-universes. Knowl-Based Syst 23(8):817–822

    Google Scholar 

  • Yang L, Xu L (2011) Topological properties of generalized approximation spaces. Inf Sci 181(17):3570–3580

    MathSciNet  Google Scholar 

  • Yang HL, Li SG, Wang S, Wang J (2012) Bipolar fuzzy rough set model on two different universes and its applications. Knowl-Based Syst 35:94–101

    Google Scholar 

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

    Google Scholar 

  • Zadeh LA (1971) Similarity relations and fuzzy orderings. Inf Sci 3:177–200

    MathSciNet  Google Scholar 

  • Zhang WR (1994) Bipolar fuzzy sets and relations: a computational framework for cognitive modeling and multiagent decision analysis. In: proceedings of industrial fuzzy control and intelligent systems conference and the NASA joint technology workshop on neural networks and fuzzy logic and fuzzy information processing society biannual conference, San Antonio, Tex, USA, pp 305–309

  • Zhang Q, Hu J, Feng J, Liu A, Li Y (2019) New similarity measures of Pythagorean fuzzy sets and their applications. IEEE Access 7(3):138192–138202

    Google Scholar 

  • Zhou L, Wu WZ, Zhang WX (2009) On intuitionistic fuzzy rough sets and their topological structures. Int J Gener Syst 6(38):589–616

    MathSciNet  Google Scholar 

  • Zhu W (2007) Generalized rough sets based on relations. Inf Sci 177(22):4997–5011

    MathSciNet  Google Scholar 

Download references

Acknowledgements

The authors extend their appreciation to the Princess Nourah bint Abdulrahman University Researchers Supporting Project number (PNURSP2024R404), Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia for funding this research work.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Saba Ayub.

Ethics declarations

Conflict of interest

The authors declare that they have no Conflict of interest.

Additional information

Publisher's Note

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

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Gul, R., Ayub, S., Shabir, M. et al. Roughness of linear Diophantine fuzzy sets by intuitionistic fuzzy relations over dual universes with decision-making applications. Comp. Appl. Math. 43, 346 (2024). https://doi.org/10.1007/s40314-024-02805-4

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s40314-024-02805-4

Keywords

Mathematics Subject Classification

Navigation