Skip to main content
Log in

Fully fuzzy linear systems with trapezoidal and hexagonal fuzzy numbers

  • Original Paper
  • Published:
Granular Computing Aims and scope Submit manuscript

Abstract

We study fully fuzzy linear systems with trapezoidal and hexagonal fuzzy numbers. The existence and uniqueness of the solution for such systems have been investigated in the literature under some restrictions on the coefficients matrix on one hand, and on the multiplication of fuzzy numbers on the other hand. Almost all researchers approximated the multiplication of two fuzzy numbers when they used the arithmetic \(\alpha -cut\). Using this approach, the multiplication of two positive fuzzy numbers need not be positive and in other times leads to a fuzzy number that is not of the same type. The aim of the current research is to solve trapezoidal and hexagonal fuzzy linear systems using the exact multiplication definition of \(\alpha -cut\) and under certain conditions on the coefficients matrices to insure that the solution is a set of positive fuzzy numbers that are trapezoidal and hexagonal, respectively. We illustrate the proposed method using a number of numerical examples. We compare the numerical results with a well-known method to show the advantages of the proposed method.

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.

Fig. 1
Fig. 2

Similar content being viewed by others

Data availability

Data sharing not applicable to this article as no data-sets were generated or analyzed during the current study.

References

  • Abbasi SMM, Jalali A (2019) A novel approach for solving fully fuzzy linear systems and their duality. J Intell Fuzzy Syst 37(2):2609–2619

    Article  Google Scholar 

  • Abidin AS, Mashadi M, Sri G (2019) Algebraic modification of trapezoidal fuzzy numbers to complete fully fuzzy linear equations system using gauss-jacobi method. Int J Manag Fuzzy Syst 5(2):40–46

    Article  Google Scholar 

  • Allahviranloo T (2004) Numerical methods for fuzzy system of linear equations. Appl Math Comput 155(2):493–502

    MathSciNet  MATH  Google Scholar 

  • Araghi MAF, Zarei E (2017) Dynamical control of computations using the iterative methods to solve fully fuzzy linear systems. Adv Fuzzy Logic Technol 641:55–68

    Google Scholar 

  • Beaula T, Mohan PL (2017) Cholesky decomposition method for solving fully fuzzy linear system of equations with trapezoidal fuzzy number. Int J Fuzzy Math Arch 14(2):261–265

    Google Scholar 

  • Beaula T, Mohan PL (2019) Fuzzified substituitional method for solving fully fuzzy linear system of equations. J Appl Sci Comput 6(5):2950–2957

    Google Scholar 

  • Buckley J, Qu Y (1991) Solving systems of linear fuzzy equations. Fuzzy Sets Syst 43(1):33–43

    Article  MathSciNet  Google Scholar 

  • Chen SM (1996) A fuzzy reasoning approach for rule-based systems based on fuzzy logics. IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) 26(5):769–778

  • Chen SM (1998) Aggregating fuzzy opinions in the group decision-making environment. Cybernet Syst 29(4):363–376

    Article  Google Scholar 

  • Chen SM, Huang CM (2003) Generating weighted fuzzy rules from relational database systems for estimating null values using genetic algorithms. IEEE Trans Fuzzy Syst 11(4):495–506

    Article  Google Scholar 

  • Chen SM, Jong WT (1997) Fuzzy query translation for relational database systems. IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) 27(4):714–721

  • Chen SM, Ko YK, Chang YC, Pan JS (2009) Weighted fuzzy interpolative reasoning based on weighted increment transformation and weighted ratio transformation techniques. IEEE Trans Fuzzy Syst 17(6):1412–1427

    Article  Google Scholar 

  • Dehghan M, Hashemi B (2006) Solution of the fully fuzzy linear systems using the decomposition procedure. Appl Math Comput 182(2):1568–1580

    MathSciNet  MATH  Google Scholar 

  • Desmita Z, Mashadi M (2019) Alternative multiplying triangular fuzzy number and applied in fully fuzzy linear system. Int J Sci 56(1):113–123

    Google Scholar 

  • Dubois D, Prade H (1978) Operations on fuzzy numbers. Int J Syst Sci 9(6):613–626

    Article  MathSciNet  Google Scholar 

  • Dubois D, Prade H (1993) Fuzzy numbers: an overview. In: Readings in Fuzzy Sets for Intelligent Systems, Elsevier, pp 112–148

  • Dubois DJ (1980) Fuzzy sets and systems: theory and applications, vol 144. Academic press

  • Eidelman Y, Milman VD, Tsolomitis A (2004) Functional analysis: an introduction, vol 66. American Mathematical Soc

  • Friedman M, Ming M, Kandel A (1998) Fuzzy linear systems. Fuzzy Sets Syst 96(2):201–209

    Article  MathSciNet  Google Scholar 

  • Gao S, Zhang Z, Cao C (2009) Multiplication operation on fuzzy numbers. JSW 4(4):331–338

    Article  Google Scholar 

  • Garg H (2018) Some arithmetic operations on the generalized sigmoidal fuzzy numbers and its application. Granular Comput 3(1):9–25

    Article  Google Scholar 

  • Garg H et al (2018) Arithmetic operations on generalized parabolic fuzzy numbers and its application. Proc Natl Acad Sci India Sect. A 88(1):15–26

    Article  MathSciNet  Google Scholar 

  • Karthik NJ, Chandrasekaran E (2013) Solving fully fuzzy linear systems with trapezoidal fuzzy number matrices by partitioning. International Journal of Computer Applications 64(9)

  • Karthik NJ, Chandrasekaran E (2014) Solving fully fuzzy linear systems with trapezoidal fuzzy number matrices by partitioning the block matrices. Ann Pure Appl Math 8(2):261–267

    Google Scholar 

  • Khalid Ak, Othman ZS (2019) A preliminary study of numerical solutions for fully fuzzy linear system. Malaysian J Ind Technol 3(1):20–26

    Google Scholar 

  • Kocken HG, Ahlatcioglu M, Albayrak I (2016) Finding the fuzzy solutions of a general fully fuzzy linear equation system. J Intell Fuzzy Syst 30(2):921–933

    Article  Google Scholar 

  • Kumar A, Neetu AB (2010) A new method to solve fully fuzzy linear system with trapezoidal fuzzy numbers. Can J Sci Eng Math 1(3):45–56

    Google Scholar 

  • Kumar A, Bansal A, Babbar N (2013) Fully fuzzy linear systems of triangular fuzzy numbers (a, b, c). International Journal of Intelligent Computing and Cybernetics

  • Malkawi G, Rida I, Ahmad N (2018) An associated linear system approach for solving fully fuzzy linear system with hexagonal fuzzy number. In: 2018 advances in science and engineering technology international conferences (ASET), IEEE, pp 1–7

  • Muruganandam S, Razak KA, Rajakumar K (2019) Solving fully fuzzy linear systems by gauss jordan elimination method. In: Journal of Physics: Conference Series, IOP Publishing, vol 1362, p 012087

  • Sari DRA, Mashadi M (2019) New arithmetic triangular fuzzy number for solving fully fuzzy linear system using inverse matrix. Int J Sci 46(2):169–180

    Google Scholar 

  • Seresht NG, Fayek AR (2019) Computational method for fuzzy arithmetic operations on triangular fuzzy numbers by extension principle. Int J Approximate Reasoning 106:172–193

    Article  MathSciNet  Google Scholar 

  • Shyi-Ming Chen, Jyh-Sheng Ke, Jin-Fu Chang (1990) Knowledge representation using fuzzy petri nets. IEEE Trans Knowl Data Eng 2(3):311–319. https://doi.org/10.1109/69.60794

    Article  Google Scholar 

  • Siahlooei E, Fazeli SAS (2018) An application of interval arithmetic for solving fully fuzzy linear systems with trapezoidal fuzzy numbers. Adv Fuzzy Syst 2018:10

    MATH  Google Scholar 

  • Sotoudeh-Anvari A (2020) A critical review on theoretical drawbacks and mathematical incorrect assumptions in fuzzy or methods: Review from 2010 to 2020. Applied Soft Computing 93

  • Vahidi J, Rezvani S (2013) Arithmetic operations on trapezoidal fuzzy numbers. J Nonlinear Anal Appl 2013:1–8

    Google Scholar 

  • Vijayalakshmi V, Surabhi S, Karpagam A (2020) Fully fuzzy linear systems in python programming. Int J Eng Adv Technol (IJEAT) 9(4):951–956

    Article  Google Scholar 

  • Zadeh LA (1965) Fuzzy sets. Inform Control 8(3):338–353

    Article  Google Scholar 

  • Zhang D, Han QL, Jia X (2015) Network-based output tracking control for t-s fuzzy systems using an event-triggered communication scheme. Fuzzy Sets Syst 273:26–48

    Article  MathSciNet  Google Scholar 

  • Zhang K, Zhan J, Wu WZ (2020) Novel fuzzy rough set models and corresponding applications to multi-criteria decision-making. Fuzzy Sets Syst 383:92–126

    Article  MathSciNet  Google Scholar 

Download references

Acknowledgements

We would like to thank the anonymous reviewers and our research group members for helpful discussions and comments. Moreover, we thank Arab American University-Palestine (AAUP) and Palestine Technical University-kadoorie (PTUK) for their continuous support.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ammar Qarariyah.

Ethics declarations

Conflicts of interest

The authors do not have any conflicts of interest to declare.

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

Ziqan, A., Ibrahim, S., Marabeh, M. et al. Fully fuzzy linear systems with trapezoidal and hexagonal fuzzy numbers. Granul. Comput. 7, 229–238 (2022). https://doi.org/10.1007/s41066-021-00262-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s41066-021-00262-6

Keywords

Navigation