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Minimal Solutions of Fuzzy Relation Equations with General Operators on the Unit Interval

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 444))

Abstract

Fuzzy relation equations arise as a mechanism to solve problems in several frameworks, such as in fuzzy logic. Moreover, the solvability of these equations has been related to fuzzy property-oriented concept lattices.

This paper studies a procedure to obtain the minimal solutions of fuzzy relation equations R ∘ X = T, with an isotone binary operation associated with a (left or right) residuated implication on the unit interval. From this study several results, based on the covering problem, are introduced generalizing other ones given in the literature.

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References

  1. Bandler, W., Kohout, L.: Semantics of implication operators and fuzzy relational products. Int. J. Man-Machine Studies 12, 89–116 (1980)

    Article  MATH  MathSciNet  Google Scholar 

  2. Bartl, E.: Fuzzy Relational Equation. Phd Dissertation. PhD thesis, Faculty of Science, Palacky University Olomouc (2013)

    Google Scholar 

  3. Bělohlávek, R.: Fuzzy Relational Systems: Foundations and Principles. Kluwer Academic Publishers (2002)

    Google Scholar 

  4. Bělohlávek, R.: Sup-t-norm and inf-residuum are one type of relational product: Unifying framework and consequences. Fuzzy Sets and Systems 197, 45–58 (2012)

    Article  MATH  MathSciNet  Google Scholar 

  5. Chen, L., Wang, P.: Fuzzy relation equations (ii): The branch-point-solutions and the categorized minimal solutions. Soft Computing - A Fusion of Foundations, Methodologies and Applications 11, 33–40 (2007)

    MATH  Google Scholar 

  6. De Baets, B.: Analytical solution methods for fuzzy relation equations. In: Dubois, D., Prade, H. (eds.) The Handbooks of Fuzzy Sets Series, vol. 1, pp. 291–340. Kluwer, Dordrecht (1999)

    Google Scholar 

  7. Di Nola, A., Sanchez, E., Pedrycz, W., Sessa, S.: Fuzzy Relation Equations and Their Applications to Knowledge Engineering. Kluwer Academic Publishers, Norwell (1989)

    Book  MATH  Google Scholar 

  8. Díaz, J., Medina, J.: Applying multi-adjoint relation equations to fuzzy logic programming. In: XV Congreso Español sobre Tecnologías y Lógica Fuzzy, ESTYLF (2014)

    Google Scholar 

  9. Díaz, J.C., Medina, J.: Concept lattices in fuzzy relation equations. In: The 8th International Conference on Concept Lattices and Their Applications, pp. 75–86 (2011)

    Google Scholar 

  10. Díaz, J.C., Medina, J.: Multi-adjoint relation equations: Definition, properties and solutions using concept lattices. Information Sciences 253, 100–109 (2013)

    Article  MathSciNet  Google Scholar 

  11. Díaz, J.C., Medina, J.: Solving systems of fuzzy relation equations by fuzzy property-oriented concepts. Information Sciences 222, 405–412 (2013)

    Article  MathSciNet  Google Scholar 

  12. Lin, J.-L.: On the relation between fuzzy max-archimedean t-norm relational equations and the covering problem. Fuzzy Sets and Systems 160(16), 2328–2344 (2009)

    Article  MATH  MathSciNet  Google Scholar 

  13. Lin, J.-L., Wu, Y.-K., Guu, S.-M.: On fuzzy relational equations and the covering problem. Information Sciences 181(14), 2951–2963 (2011)

    Article  MATH  MathSciNet  Google Scholar 

  14. Markovskii, A.: On the relation between equations with max-product composition and the covering problem. Fuzzy Sets and Systems 153(2), 261–273 (2005)

    Article  MATH  MathSciNet  Google Scholar 

  15. Medina, J., Ojeda-Aciego, M., Vojtáš, P.: Multi-adjoint logic programming with continuous semantics. In: Eiter, T., Faber, W., Truszczyński, M. (eds.) LPNMR 2001. LNCS (LNAI), vol. 2173, pp. 351–364. Springer, Heidelberg (2001)

    Google Scholar 

  16. Peeva, K.: Resolution of fuzzy relational equations: Method, algorithm and software with applications. Information Sciences 234, 44–63 (2013)

    Article  MATH  MathSciNet  Google Scholar 

  17. Perfilieva, I., Nosková, L.: System of fuzzy relation equations with inf-→ composition: Complete set of solutions. Fuzzy Sets and Systems 159(17), 2256–2271 (2008)

    Article  MATH  MathSciNet  Google Scholar 

  18. Sanchez, E.: Resolution of composite fuzzy relation equations. Information and Control 30(1), 38–48 (1976)

    Article  MATH  MathSciNet  Google Scholar 

  19. Shieh, B.-S.: Solution to the covering problem. Information Sciences 222, 626–633 (2013)

    Article  MathSciNet  Google Scholar 

  20. Turunen, E.: On generalized fuzzy relation equations: necessary and sufficient conditions for the existence of solutions. Acta Universitatis Carolinae. Mathematica et Physica 028(1), 33–37 (1987)

    MathSciNet  Google Scholar 

  21. Yeh, C.-T.: On the minimal solutions of max-min fuzzy relational equations. Fuzzy Sets and Systems 159(1), 23–39 (2008)

    Article  MATH  MathSciNet  Google Scholar 

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Medina, J., Turunen, E., Bartl, E., Díaz-Moreno, J.C. (2014). Minimal Solutions of Fuzzy Relation Equations with General Operators on the Unit Interval. In: Laurent, A., Strauss, O., Bouchon-Meunier, B., Yager, R.R. (eds) Information Processing and Management of Uncertainty in Knowledge-Based Systems. IPMU 2014. Communications in Computer and Information Science, vol 444. Springer, Cham. https://doi.org/10.1007/978-3-319-08852-5_9

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  • DOI: https://doi.org/10.1007/978-3-319-08852-5_9

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-08851-8

  • Online ISBN: 978-3-319-08852-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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