Skip to main content

Fuzzy Interval Analysis

  • Chapter
Fundamentals of Fuzzy Sets

Part of the book series: The Handbooks of Fuzzy Sets Series ((FSHS,volume 7))

Abstract

This chapter is an overview of past and present works dealing with fuzzy intervals and their operations. A fuzzy interval is a fuzzy set in the real line whose level-cuts are intervals. Particular cases include usual real numbers and intervals. Usual operations on the real line canonically extend to operations between fuzzy quantities, thus extending the usual interval (or error) analysis to membership functions. What is obtained is a counterpart of random variable calculus, but where, contrary to the latter case, there is no compensation between variables. Many results pertaining to basic properties of fuzzy interval analysis are summed up in the chapter. Computational methods are presented, exact or approximate ones, based on parametric representations, or level-cut approximations. The generalized fuzzy variable calculus involving interactive variables is also discussed with emphasis on triangular-norm based fuzzy additions. Dual ‘optimistic’ operations on fuzzy intervals, i.e., with maximal error compensation are also presented; its interest lies in providing tools for solving fuzzy interval equations. This chapter also contains a reasoned survey of methods for comparing and ranking fuzzy intervals. The chapter includes some historical background, as well as pointers to applications in mathematics and engineering.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  • Adamo J. M. (1980). Fuzzy decision trees, Fuzzy Sets and Systems, 4, 207–219.

    Article  MathSciNet  MATH  Google Scholar 

  • Ammar S. (1989). Determining the’ best1 decision in the presence of imprecise information, Fuzzy Sets and Systems, 29, 293–302.

    Article  MathSciNet  MATH  Google Scholar 

  • Anile A. M., Deodato S. and Privitera G. (1995). Implementing fuzzy arithmetic, Fuzzy Sets and Systems, 72, 239–250.

    Article  Google Scholar 

  • Antonsson E. and Otto K. (1995). Imprecision in engineering design, ASME J. of Mechanical Design, 117(B), 25–32.

    Article  Google Scholar 

  • Ambrosio R. and Martini G. B. (1984). Maximum and minimum between fuzzy symbols in non-interactive and weakly non-interactive situations, Fuzzy Sets and Systems, 12, 27–35.

    Article  MathSciNet  MATH  Google Scholar 

  • Aumann R. J. (1965). Integrals of set-valued functions, J. Math. Anal Appl., 12, 1–22.

    Article  MathSciNet  MATH  Google Scholar 

  • Baas S. M. and Kwakernaak H. (1977). Rating and ranking of multiple aspect alternatives using fuzzy sets, Automatica, 13, 47–58.

    Article  MathSciNet  MATH  Google Scholar 

  • Badard R. (1982). The law of large numbers for fuzzy processes and the estimation problem, Information Sciences, 28, 161–178.

    Article  MathSciNet  MATH  Google Scholar 

  • Badard R. (1984). Fixed point theorems for fuzzy numbers, Fuzzy Sets and Systems, 13, 291–302.

    Article  MathSciNet  MATH  Google Scholar 

  • Baekeland R. and Kerre E., (1988). Pieccwise linear fuzzy quantities: A way to implement fuzzy information into expert systems and fuzzy databases, Uncertainty and Intelligent Systems (Bouchon B., Saitta L. and Yager R. R., eds.), Lecture Notes in Computer Sciences, vol. 313, Springer-Verlag, Berlin, 119–126.

    Google Scholar 

  • Baldwin J. F. and Guild N. C. F. (1979a). Comparison of fuzzy sets on the same decision space, Fuzzy Sets and Systems, 2, 213–231.

    Article  MathSciNet  MATH  Google Scholar 

  • Baldwin J. F. and Guild N. C. F. (1979b). Comments on the fuzzy max operator of Dubois and Prade, Int. J. Systems Science, 10, 1063–1064.

    Article  MathSciNet  MATH  Google Scholar 

  • Ban J. (1990). Radon-Nikodym theorem and conditional expectation of fuzzy-valued measures and variables, Fuzzy Sets and Systems, 34, 383–392.

    Article  MathSciNet  MATH  Google Scholar 

  • Ban J. (1991). Ergodic theorems for random compact sets and fuzzy variables in Banach spaces, Fuzzy Sets and Systems, 44, 71–82.

    Article  MathSciNet  MATH  Google Scholar 

  • Baptistella L.F.B., and Ollero A. (1980). Fuzzy methodologies for interactive multicriteria optimization, IEEE Trans. Syst. Man Cybern., 10, 355–365.

    Article  MathSciNet  MATH  Google Scholar 

  • Bellman R. (1957). Dynamic Programming, Princeton University Press, Princeton, N.J.

    Google Scholar 

  • Bertoluzza C. and Bodini A. (1998). A new proof of Nguyen’s compatibility theorem in a more general context, Fuzzy Sets and Systems, 95, 99–102.

    Article  MathSciNet  MATH  Google Scholar 

  • Bertoluzza C., Corral N. and Salas AA (1995). On a new class of distances between fuzzy numbers, Mathware and Soft Computing, 2, 71–84.

    MathSciNet  MATH  Google Scholar 

  • Bezdek J.C., Dubois D. and Prade H. (Eds.) (1999). Fuzzy Sets in Approximate Reasoning and Information Systems. The Handbooks of Fuzzy Sets Series (Dubois D. and Prade H., eds.), Kluwer Acad. Publ., Boston.

    Google Scholar 

  • Biacino L. and Lettieri A. (1989). Equations with fuzzy numbers, Information Sciences, 47, 63–76.

    Article  MathSciNet  Google Scholar 

  • Bilgic T. and Türksen L.B. (1999). Measurement of membership functions: Theoretical and empirical work, Fundamentals of Fuzzy Sets (Dubois D. and Prade H. eds.), Kiuwer Acad. PubL, 1999. This volume.

    Google Scholar 

  • Bloch I. and Maitre H. (1994). Fuzzy mathematical morphology, Annals of Mathematics and Artificial Intelligence, 10, 55–84.

    Article  MathSciNet  Google Scholar 

  • Bloch L. and Maitre H. (1995). Fuzzy mathematical morphologies: A comparative study, Pattern Recognition, 28, 1341–1387.

    Article  MathSciNet  Google Scholar 

  • Bodenhofer U. (1998). A similarity-based generalisation of fuzzy orderings, PhD Thesis, J. Kepler University, Linz, Austria

    Google Scholar 

  • Boender C., De Graan J. G and Lootsma F. (1989). Multicriteria decision analysis with fuzzy pairwise comparisons, Fuzzy Sets and Systems, 29, 133–144.

    Article  MathSciNet  MATH  Google Scholar 

  • Bortolan G. and Degani R. (1985). A review of some methods for ranking fuzzy subsets, Fuzzy Sets and Systems, 15, 1–19.

    Article  MathSciNet  MATH  Google Scholar 

  • Bosc P., Buckles B.B., Petry F. E. and Pivert O. (1999). Fuzzy databases, Fuzzy Sets in Approximate Reasoning and Information Systems (Bezdek J.C., Dubois D. and Prade H., eds.), Kluwer Acad. Publ., New York, 403–468.

    Chapter  Google Scholar 

  • Bouchon-Meunier B., Kosheleva O., Kreinovich V. and Nguyen, H. T. (1997). Fuzzy numbers are the only fuzzy sets that keep invertible operations invertible, Fuzzy Sets and Systems, 91, 155–163.

    Article  MathSciNet  MATH  Google Scholar 

  • Braae M. and Rutherford D.A. (1978). Fuzzy relations in a control setting, Kybemetes, 7, 185–188.

    MATH  Google Scholar 

  • Buckles B. P. and Petry F. E. (1984). Extending the fuzzy data base with fuzzy numbers, Information Sciences, 34, 145–155.

    Article  MathSciNet  MATH  Google Scholar 

  • Buckley J. J. (1985). Ranking alternatives using fuzzy numbers, Fuzzy Sets and Systems, 15, 21–31.

    Article  MathSciNet  MATH  Google Scholar 

  • Buckley J. J. (1989a). On the algebra of interactive fuzzy numbers, Fuzzy Sets and Systems, 32, 291–306.

    Article  MathSciNet  MATH  Google Scholar 

  • Buckley J. J. (1989b). A fuzzy ranking of fuzzy numbers, Fuzzy Sets and Systems, 33, 119–122.

    Article  MathSciNet  MATH  Google Scholar 

  • Buckley J. J., (1989c). Fuzzy complex numbers, Fuzzy Sets and Systems, 33, 333–345.

    Article  MathSciNet  MATH  Google Scholar 

  • Buckley J. J. (1990). On the algebra of interactive fuzzy numbers: The continuous case, Fuzzy Sets and Systems, 37, 317–326.

    Article  MathSciNet  MATH  Google Scholar 

  • Buckley J. J. (1991). Fuzzy complex analysis I: Differentiation, Fuzzy Sets and Systems, 41, 269–284.

    Article  MathSciNet  MATH  Google Scholar 

  • Buckley J. J. (1992). Fuzzy complex analysis II: Integration, Fuzzy Sets and Systems, 49, 171–179.

    Article  MathSciNet  MATH  Google Scholar 

  • Buckley J. J. and Ghanas S. (1989). A fast method of ranking alternatives using fuzzy numbers, Fuzzy Sets and Systems, 30, 337–338.

    Article  MathSciNet  MATH  Google Scholar 

  • Buckley J. J. and Qu Y. (1990). Solving linear and quadratic fuzzy equations, Fuzzy Sets and Systems, 38, 43–61.

    Article  MathSciNet  MATH  Google Scholar 

  • Buckley J. J. and Qu Y. (1991a). Solving fuzzy equations: a new solution concept, Fuzzy Sets and Systems, 39, 291–303.

    Article  MathSciNet  MATH  Google Scholar 

  • Buckley J. J. and Qu Y. (1991b), Solving systems of linear fuzzy equations, Fuzzy Sets and Systems, 43, 33–44.

    Article  MathSciNet  MATH  Google Scholar 

  • Burgin M. (1995). Nonclassical analysis: Fuzzy continuity and convergence, Fuzzy Sets and Systems, 75, 291–299.

    Article  MathSciNet  MATH  Google Scholar 

  • Burgin M. and Sostak M. (1994). Fuzzyfication of the theory of continuous functions, Fuzzy Sets and Systems, 64, 71–81.

    Article  MathSciNet  Google Scholar 

  • Campos L. and Gonzalez (1994). Further contributions to the study of average value for ranking fuzzy numbers, Int. J. Approximate Reasoning, 10, 135–163.

    Article  MathSciNet  MATH  Google Scholar 

  • Campos L. and Verdegay J. L. (1989). Linear programming problems and ranking of fuzzy numbers, Fuzzy Sets and Systems, 32, 1–12.

    Article  MathSciNet  MATH  Google Scholar 

  • Cayrol M., Farreny H. and Prade H. (1982). Fuzzy pattern matching, Kybernetes, 11, 103–116.

    Article  Google Scholar 

  • Ghanas S., De Igado M., Verdegay M., and Vila M.A. (1993). Ranking fuzzy intervals in the setting of random sets, Information Sciences, 69, 201–217.

    Article  MathSciNet  Google Scholar 

  • Ghanas S. and Kamburovski J. (1981). The use of fuzzy variables in PERT, Fuzzy Sets and Systems, 3, 11–19.

    Google Scholar 

  • Ghanas S. and Kolodziejczyk W. (1982). Maximum flow in a network with fuzzy arc capacities, Fuzzy Sets and Systems, 8, 165–173.

    Article  MathSciNet  Google Scholar 

  • Ghanas S. and Kuchta D. (1998), Discrete fuzzy optimization, Fuzzy Sets in Decision Analysis Operations Research and Statistics (Slowinski R., ed.), The Handbooks of Fuzzy Sets Series, Kluwer, Boston, USA.

    Google Scholar 

  • Ghanas S. and Nowakowski M. (1988), Single value simulation of fuzzy variable, Fuzzy Sets and Systems, 25, 43–57.

    Article  MathSciNet  Google Scholar 

  • Chang P. T. and Lee E. S. (1994). Fuzzy arithmetics and comparison of fuzzy numbers, Fuzzy Optimization: Recent Advances (De lgado M, Kacprzyk J., Verdegay J. L., Vila M. A., eds), Physica-Verlag, Heidelberg, Germany, 69–81.

    Google Scholar 

  • Chang W. (1981). Ranking of fuzzy utilities with triangular membership functions. Proc. Int. Conf. on Policy Analysis and Information Systems, Taipei, 263–271.

    Google Scholar 

  • Chen S. H. (1985). Ranking fuzzy numbers with maximizing sets and minimizing sets, Fuzzy Sets and Systems, 17, 113–129.

    Article  MathSciNet  MATH  Google Scholar 

  • Chen S. J., Hwang, C. L. and Hwang, F. P. (1992). Fuzzy Multiple Attribute Decision Making-Methods and Applications, Lecture Notes in Economics and Mathematical Systems, vol. 375, Springer Verlag, Berlin.

    Google Scholar 

  • Chen H. K., Hsu W. K. and Chiang W. L. (1998). A comparison of the vertex method and with JHE method, Fuzzy Sets and Systems, 95, 201–214.

    Article  MathSciNet  Google Scholar 

  • Cheng C. H. (1998). A new approach for ranking fuzzy numbers by distance method, Fuzzy Sets and Systems, 95, 307–317.

    Article  MathSciNet  MATH  Google Scholar 

  • Choobineh F. and Li H. (1993). An index for ordering fuzzy numbers, Fuzzy Sets and Systems, 54, 287–295.

    Article  MathSciNet  Google Scholar 

  • Cuninghame-Green R. A. (1979). Minimax Algebra, Lecture Notes in Economical and Mathematical Systems, vol. 166, Springer-Verlag, Berlin.

    Google Scholar 

  • Cuninghame-Green R. A. and Cechlarova V. (1995). Residuation in fuzzy algebra and some applications, Fuzzy Sets and Systems, 71, 227–239.

    Article  MathSciNet  MATH  Google Scholar 

  • Czogala E. and Hirota K. (1986). Probabilistic Sets: Fuzzy and Stochastic Approach to Decision Control and Recognition Processes, ISR 91, Verlag TUV Rheinland, Köln.

    Google Scholar 

  • De Baets B. (1999). Analytical solution methods for fuzzy relational equations, Fundamentals of Fuzzy Sets (Dubois D. and Prade H., eds.), Kluwer Acad. Publ., 1999. This volume.

    Google Scholar 

  • De Baets, B., Kerre E. and Gupta M. M. (1994a). The fundamentals of fuzzy mathematical morphology — Part 1: Basic concepts, Int. J. General Systems, 23, 155–171.

    Article  Google Scholar 

  • De Baets, B., Kerre E. and Gupta M. M. (1994b). The fundamentals of fuzzy mathematical morphology — Part 2: Idempotence, convexity and decomposition, Int. J, General Systems, 23, 307–322.

    Article  Google Scholar 

  • De Baets, B., Mares, M. and Mesiar, R. (1997). T-partitions of the real line generated by idempotents shapes, Fuzzy Sets and Systems, 91, 177–184.

    Article  MathSciNet  MATH  Google Scholar 

  • De Baets B., and Markova-Stupnanova A. (1997). Analytical expressions for the addition of fuzzy intervals, Fuzzy Sets and Systems, 91, 203–213.

    Article  MathSciNet  MATH  Google Scholar 

  • De Campos Ibanez L.M. and Gonzalez-Munoz (1989). A subjective approach for ranking fuzzy numbers, Fuzzy Sets and Systems, 29, 145–154.

    Article  MathSciNet  MATH  Google Scholar 

  • De lgado M., Verdegay J. L. and Vila M. A (1988). A procedure for ranking fuzzy-numbers using fuzzy relations, Fuzzy Sets and Systems, 26, 49–62.

    Article  MathSciNet  Google Scholar 

  • De lgado M., Verdegay J. L. and Vila M. A (1994). Fuzzy numbers, definitions and properties, Mathware and Soft Computing, 1, 31–43.

    MathSciNet  Google Scholar 

  • De lgado M., Vila M. A. and Voxman W. (1998a). On a canonical representation for fuzzy numbers, Fuzzy Sets and Systems, 93, 125–135.

    Article  MathSciNet  Google Scholar 

  • De lgado M., Vila M. A., and Voxman W. (1998b). A fuzziness measure for fuzzy numbers: Applications, Fuzzy Sets and Systems, 94, 205–216.

    Article  MathSciNet  Google Scholar 

  • De mpster A. P. (1967). Upper and lower probabilities induced by a multivalued mapping, Ann. Math. Stau, 38, 325–339.

    Article  Google Scholar 

  • De nneberg D. (1994). Nonadditive Measure and Integral, Kluwer Academic, Dordrecht, The Netherlands.

    Google Scholar 

  • Diamond P. and Kloeden P. (1994). Metric spaces of fuzzy sets, World Scientific, Singapore.

    MATH  Google Scholar 

  • Dijkman J. G., van Haeringen H. and de Lange S. T. (1983), Fuzzy numbers, J. Math. Anal Appl., 92, 301–341.

    Article  MathSciNet  MATH  Google Scholar 

  • Dishkant H. (1981). About membership functions estimation, Fuzzy Sets and Systems, 5, 141–147.

    Article  MathSciNet  MATH  Google Scholar 

  • Dombi J. (1986). Properties of the fuzzy connectives in the light of general representation theory, Acta Cybernetica, 7, 313–321.

    MathSciNet  MATH  Google Scholar 

  • Dong W. and Shah H. (1987). Vertex method for computing functions of fuzzy variables, Fuzzy Sets and Systems, 24, 65–79.

    Article  MathSciNet  MATH  Google Scholar 

  • Dong W., Shah H. and Wong F. (1985). Fuzzy computations in decision and risk analysis, Civ. Eng. Syst., 2, 201–208.

    Article  Google Scholar 

  • Dong W. and Wong F. (1987). Fuzzy weighted averages and the implementation of the extension principle, Fuzzy Sets and Systems, 21, 183–201.

    Article  MathSciNet  MATH  Google Scholar 

  • Dong W. and Wong F. (1989). Interactive variables and fuzzy decisions, Fuzzy Sets and Systems, 29, 1–19.

    Article  MathSciNet  MATH  Google Scholar 

  • Dubois D. (1982). A law of large numbers for nonconvex fuzzy sets of the real line, Busefal (IRIT, Université P. Sabatier, Toulouse), 9, 31–38.

    MATH  Google Scholar 

  • Dubois D. (1983). A fuzzy heuristic, interactive approach to the optimal network problem, Advances in Fuzzy Sets and Possibility Theory and Applications (Wang P. P., ed.), Plenum Press, New York, 253–276.

    Chapter  Google Scholar 

  • Dubois D. (1987a). An application of fuzzy arithmetics to the optimization of industrial machining processes, Mathematical Modelling, 9, 461–475.

    Article  MathSciNet  MATH  Google Scholar 

  • Dubois D. (1987b). Linear programming with fuzzy data, Analysis of Fuzzy Information (Bezdek J. C, ed.), Vol. 3, CRC Press, Boca Raton, F1., 241–264.

    Google Scholar 

  • Dubois D., Fargier H., and Prade (1995). Fuzzy constraints in job-shop scheduling, J. Intellig. Manufacturing, 6, 215–234.

    Article  Google Scholar 

  • DuboisD., Nguyen H.T. and Prade H. (1999). Possibility theory, probability and fuzzy sets: Misunderstandings, bridges and gaps, Fundamentals of Fuzzy Sets (Dubois D. and Prade H., eds.), Kluwer Acad. Publ., 1999. This volume.

    Google Scholar 

  • Dubois D., Ostasiewicz W. and Prade H. (1999). Fuzzy sets: History and basic notions, Fundamentals of Fuzzy Sets (Dubois D. and Prade H., eds.), Kluwer Acad. Publ., 1999. This volume.

    Google Scholar 

  • Dubois D. and Prade H. (1978a). Operations on fuzzy numbers, Int. J. Systems Science, 9, 613–626.

    Article  MathSciNet  MATH  Google Scholar 

  • Dubois D. and Prade H. (1978b). Comment on Tolerance analysis using fuzzy sets’ and ‘A procedure for multiple aspect decision making’, Int. J. Systems Science., 9, 357–360.

    Article  MathSciNet  MATH  Google Scholar 

  • Dubois D. and Prade H. (1978c). Algorithmes de plus court chemin pour traiter des donnees floues, RAIRO, Serie R. O., 12, 213–227.

    MATH  Google Scholar 

  • Dubois D. and Prade H. (1979a). Fuzzy real algebra: Some results, Fuzzy Sets and Systems, 2, 327–348.

    Article  MathSciNet  MATH  Google Scholar 

  • Dubois D. and Prade H. (1979b), Operations in a fuzzy-valued logic, Inf. & Control, 43, 224–240.

    Article  MathSciNet  MATH  Google Scholar 

  • Dubois D. and Prade H. (1980a). Fuzzy Sets and Systems: Theory and Applications, Academic Press, New York.

    MATH  Google Scholar 

  • Dubois D. and Prade H. (1980b). Systems of linear fuzzy constraints, Fuzzy Sets and Systems, 3, 37–48.

    Article  MathSciNet  MATH  Google Scholar 

  • Dubois D. and Prade H. (1981). Additions of interactive fuzzy numbers, IEEE Trans. Automatic Control, 26, 926–936.

    Article  MathSciNet  Google Scholar 

  • Dubois D. and Prade H. (1982a). The use of fuzzy numbers in decision analysis, Fuzzy Information and Decision Processes (Gupta M. M. and Sanchez E., eds.), North-Holland, Amsterdam, 309–321.

    Google Scholar 

  • Dubois D., and Prade H. (1982b). Towards fuzzy differential calculus, Fuzzy Sets and Systems, 8, Part I. Integration of fuzzy mappings, 1-17; Part II. Integration on fuzzy intervals, 105-116; Part III Differentiation, 225–233.

    Google Scholar 

  • Dubois D. and Prade H. (1982c). What does’ convergence’ mean for fuzzy numbers?, Proc. IFAC Symp. on Theory and Applications of Digital Control (Mahalonabis A. K., ed.), Pergamon Press, New York, 433–438.

    Google Scholar 

  • Dubois D. and Prade H. (1983a). Inverse operations for fuzzy numbers, Proc. IFAC Symp. on Fuzzy Information, Knowledge Representation and Decision Processes (Sanchez E. and Gupta M. M., eds.), Pergamon Press, Oxford, 391–396.

    Google Scholar 

  • Dubois D. and Prade H. (1983b). Ranking fuzzy numbers in the setting of possibility theory, Information Sciences, 30, 183–224.

    Article  MathSciNet  MATH  Google Scholar 

  • Dubois D. and Prade H. (1983c). Twofold fuzzy sets: An approach to the representation of sets with fuzzy boundaries, based on possibility and necessity measures, Fuzzy Math. (Huazhong, China), 3(4), 53–76.

    MathSciNet  MATH  Google Scholar 

  • Dubois D. and Prade H. (1983d). On distances between fuzzy points and their use for plausible reasoning, IEEE Int. Conf. on Systems Man and Cybernetics, Bombay and New De lhi, IEEE, Pistacaway, NJ, 300–303.

    Google Scholar 

  • Dubois D. and Prade H. (1984). Fuzzy set-theoretic differences and inclusions and their use in the analysis of fuzzy equations, Control Cybern. (Warsaw), 13, 129–146.

    MathSciNet  MATH  Google Scholar 

  • Dubois D. and Prade H. (1985), Fuzzy cardinality and the modeling of imprecise quantification, Fuzzy Sets and Systems, 16, 199–230.

    Article  MathSciNet  MATH  Google Scholar 

  • Dubois D. and Prade H. (1986). Fuzzy sets and statistical data, Europ. J. Op. Res., 25, 345–356.

    Article  MathSciNet  MATH  Google Scholar 

  • Dubois D. and Prade H. (1987a). Fuzzy numbers: An overview, Analysis of Fuzzy Information, Vol. I (Bezdek J., ed.), CRC Press, Boca Raton, FL, 3–39.

    Google Scholar 

  • Dubois D. and Prade H., (1987b). The mean value of a fuzzy number. Fuzzy Sets and Systems, 24, 279–300.

    Article  MathSciNet  MATH  Google Scholar 

  • Dubois D. and Prade H,, (eds.) (1987c). Special Issue on Fuzzy Numbers. Fuzzy Sets and Systems, 24(3).

    Google Scholar 

  • Dubois D. and Prade H. (1988a). Possibility Theory. An Approach to Computerized Processing of Uncertainty. Plenum Press, New York.

    MATH  Google Scholar 

  • Dubois D. and Prade H. (1988b). On fuzzy syllogisms, Computational Intelligence, 4, 171–179.

    Article  Google Scholar 

  • Dubois D. and Prade H. (1989a). Processing fuzzy temporal knowledge, IEEE Trans. Syst. Man and Cybern., 19, 729–744.

    Article  MathSciNet  Google Scholar 

  • Dubois D. and Prade H. (1989b). Order-of-magnitude reasoning with fuzzy relations, Revue d’Intelligence Artificielle (Hermes, Paris), 3(4), 69–94.

    Google Scholar 

  • Dubois D. and Prade H. (1991a). Random sets and fuzzy interval analysis, Fuzzy Sets and Systems, 42, 87–101.

    Article  MathSciNet  MATH  Google Scholar 

  • Dubois D. and Prade H. (1991b). On the ranking of ill-known values in possibility theory, Fuzzy Sets and Systems, 43, 311–317.

    Article  MathSciNet  MATH  Google Scholar 

  • Dubois D. and Prade H. (1995). Possibility theory as a basis for qualitative decision theory. Proc. 24 th Int. Joint Conf. on AI, Montreal, Canada, 1924–1930.

    Google Scholar 

  • Dubois D., Prade H. and Sandri S. (1993). On possibility/probability transformations. In: Fuzzy Logic. State of the Art, (R. Lowen, M. Roubens, eds.), Kluwer Acad. Publ., Dordrecht, 103–112.

    Google Scholar 

  • Dubois D., Prade F.L. and Sabbadin R. (1998). Qualitative decision theory with Sugeno integrals. Proc. of the 14th Conf. on Uncertainty in Artificial Intelligence, Madison, July 24-26, 1998, (G. Cooper, S. Moral, eds.), Morgan Kaufmann, San Francisco, 121–128.

    Google Scholar 

  • Dubois D., Prade H. and Yager R. R. (1998). Computation of intelligent fusion operations based on constrained fuzzy arithmetic, Proc. IEEE Int. Conf. on Fuzzy Systems, Anchorage, Al., 767–772.

    Google Scholar 

  • Efstathiou J. and Bonissone P. (1979). Ranking fuzzy sets using linguistic preference relations, Proc. IEEE Int. Conf. on Systems Man and Cybern. Denver, Co, USA.

    Google Scholar 

  • Efstathiou J. and Tong R. (1982). Ranking fuzzy sets: A decision-theoretic approach, IEEE Trans. SysL Man. Cybern., 12, 655–659.

    Article  MathSciNet  Google Scholar 

  • Eklund P. and Gähler W. (1988). Basic notions for fuzzy topology, Fuzzy Sets and Systems, 26, 333–356.

    Article  MathSciNet  MATH  Google Scholar 

  • Féron R. (1976). Ensembles aléatoires flous, C.R. Acad. Sci. Ser A., 282, 903–906.

    MATH  Google Scholar 

  • Fishburn P. (1985). Interval Orders and Interval Graphs. Wiley, New-York.

    Google Scholar 

  • Jenei S. and Fodor J. (1998). On continuous triangular norms, Fuzzy Sets and Systems, 100, 273–282.

    Article  MathSciNet  MATH  Google Scholar 

  • Fodor J., Orlovski S.A., Perny P. and Roubens M. (1998). The use of fuzzy preference models in multiple criteria choice, ranking and sorting, Fuzzy Sets in Decision Analysis, Operations Research and Statistics (Slowinski R., ed.), Kluwer Acad. Publ., Boston, 69–101.

    Chapter  Google Scholar 

  • Fodor J. and Roubens M. (1994). Fuzzy Preference Modelling and Multicriteria Decision Support, Kluwer Acad. Publ., Dordrecht.

    Google Scholar 

  • Fodor J. and Yager R.R. (1999). Fuzzy set-theoretic operators and quantifiers, Fundamentals of Fuzzy Sets (Dubois D. and Prade H., eds.), Kluwer Acad, Publ., 1999. This volume.

    Google Scholar 

  • Fortemps P. (1997). Jobshop scheduling with imprecise durations: A fuzzy approach, IEEE Trans. Fuzzy Systems, 5, 557–569.

    Article  Google Scholar 

  • Fortemps P. and Roubens M. (1996). Ranking and defuzzification methods based on area compensation, Fuzzy Sets and Systems, 82, 319–330.

    Article  MathSciNet  MATH  Google Scholar 

  • Freeling A. N. S. (1980). Fuzzy sets and decision analysis, IEEE Trans. Syst. Man. Cybern., 10, 341–354.

    Article  Google Scholar 

  • Freeling A. N. S. (1984). Possibilities versus fuzzy probabilities-Two alternative decision-aids, Fuzzy Sets and Decision Analysis (Zimmermann H. J., Zadeh L. A. and Gaines B. R., eds.), TIMS Studies in the Management Sciences, vol. 20, North-Holland, Amsterdam, 67–71.

    Google Scholar 

  • French S. (1984). Fuzzy decision analysis: some criticisms, Fuzzy Sets and Decision Analysis (Zimmermann H. J., Zadeh L. A. and Gaines B. R,, eds.), TIMS Studies in the Management Sciences, vol. 20, North-Holland, Amsterdam, 29–44.

    Google Scholar 

  • Fullér R. (1990). On stability in possibilistic linear equality systems with Lipschitzian fuzzy numbers, Fuzzy Sets and Systems, 34, 347–354.

    Article  MathSciNet  MATH  Google Scholar 

  • Fullér R. (1991). On product-sum of triangular fuzzy numbers, Fuzzy Sets and Systems, 41, 83–87.

    Article  MathSciNet  MATH  Google Scholar 

  • Fullér R. (1992). A law of large numbers for fuzzy numbers, Fuzzy Sets and Systems, 45, 299–303.

    Article  MathSciNet  MATH  Google Scholar 

  • Fullér R. and Keresztfalvi T. (1991). On generalization of Nguyen’s theorem, Fuzzy Sets and Systems, 41, 371–374.

    Article  MathSciNet  MATH  Google Scholar 

  • Fullér R. and Keresztfalvi T. (1992). T-norm-based addition of fuzzy intervals, Fuzzy Sets and Systems, 51, 155–159.

    Article  MathSciNet  Google Scholar 

  • Fullér R. and Mesiar R. (eds.) (1997). Special Issue on Fuzzy Arithmetic, Fuzzy Sets and Systems, 91(2).

    Google Scholar 

  • Fullér R. and Triesch E. (1993). A note on the law of large numbers for fuzzy variables, Fuzzy Sets and Systems, 55, 235–236.

    Article  MathSciNet  MATH  Google Scholar 

  • Fullér R. and Zimmermann H. J. (1992). On computation of the compositional rule of inference under triangular norms, Fuzzy Sets and Systems, 51, 267–275.

    Article  MathSciNet  MATH  Google Scholar 

  • Fullér R. and Zimmermann H. J. (1993). Fuzzy reasoning for solving fuzzy mathematical programming problems, Fuzzy Sets and Systems, 60, 121–133.

    Article  MathSciNet  MATH  Google Scholar 

  • Gähler S. and Gähler W. (1994). Fuzzy real numbers, Fuzzy Sets and Systems, 66, 137–158.

    Article  MathSciNet  MATH  Google Scholar 

  • Gähler W. (1992). Fuzzy topology in Topology, Measures and Fractals, Math. Research, 67, Academia-Verlag, Berlin, 188–197.

    Google Scholar 

  • Gebhardt A. (1995). On types of fuzzy numbers and extension principles, Fuzzy Sets and Systems, 75, 311–318.

    Article  MathSciNet  MATH  Google Scholar 

  • Gebhardt J., Gil M. A. and Kruse R. (1998). Fuzzy set-theoretic methods in statistics, Fuzzy Sets in Decision Analysis, Operations Research and Statistics, The Handbook of Fuzzy Sets Serie, Kluwer Academic Publ., Dordrecht, The Netherlands, 311–348.

    Google Scholar 

  • Giachetti R. E. (1996). The Mathematics of Triangular Fuzzy Numbers to support a Model of Imprecision in Design, Ph.D. Dissertation, Industrial Engineering, North-Carolina State University, US.

    Google Scholar 

  • Giachetti R. E. and Young R. E. (1997a). Analysis of the error in standard approximation for multiplication of triangular and trapezoidal fuzzy numbers, and the development of a new approximation, Fuzzy Sets and Systems, 91, 1–15.

    Article  MathSciNet  MATH  Google Scholar 

  • Giachetti R. E. and Young R. E. (1997b). A parametric representation of fuzzy numbers and their arithmetic operators, Fuzzy Sets and Systems, 91, 185–202.

    Article  MathSciNet  MATH  Google Scholar 

  • Gil M. A. (1992), A note on the connection between fuzzy numbers and random intervals, Statistics and Probability Lett., 13, 311–319.

    Article  MATH  Google Scholar 

  • Goetschel R. H. (1997). Representations with fuzzy darts, Fuzzy Sets and Systems, 89, 77–106.

    Article  MathSciNet  MATH  Google Scholar 

  • Goetschel R. Jr. and Voxman W. (1983). Topological properties of fuzzy numbers, Fuzzy Sets and Systems, 10, 87–99.

    Article  MathSciNet  MATH  Google Scholar 

  • Gonzalez A. (1990). A study of the ranking function approach through mean values, Fuzzy Sets and Systems, 35, 29–43.

    Article  MathSciNet  MATH  Google Scholar 

  • Gonzalez A. and Vila M. A. (1991). A discrete method for studying indifference and order relations between fuzzy numbers, Information Sciences, 56, 245–258.

    Article  MathSciNet  MATH  Google Scholar 

  • Gonzalez A. and Vila M. A. (1992). Dominance relations on fuzzy numbers, Information Sciences, 64, 1–16.

    Article  MathSciNet  MATH  Google Scholar 

  • Gottwald S. (1984). On the existence of solutions of systems of fuzzy equations, Fuzzy Sets and Systems, 12, 301–302.

    Article  MathSciNet  MATH  Google Scholar 

  • Gottwald S. (1993). Fuzzy Sets and Fuzzy Logic, Vieweg, Braunschweig.

    Google Scholar 

  • Guh Y.Y., Hong C.C., Wang K.M. and Lee E.S. (1996). Fuzzy weighted average: A max-min paired elimination method, Computers Math. Applic., 32, 115–123.

    Article  MATH  Google Scholar 

  • Harman B. (1992a). On associativity of the product of modified real fuzzy numbers, Tatra Mount Math Publ., 1, 45–50.

    MathSciNet  MATH  Google Scholar 

  • Harman B. (1992b). Sum and product of the modified real fuzzy numbers, Kybernetika (Prague), Suppl. 28(1/6), 37–40.

    MathSciNet  MATH  Google Scholar 

  • Hellendoorn H. (1990). Closure properties of the compositional rule of inference, Fuzzy Sets and Systems, 35, 163–184.

    Article  MathSciNet  MATH  Google Scholar 

  • Heilpern S. (1992). The expected value of a fuzzy number, Fuzzy Sets and Systems, 47, 81–87.

    Article  MathSciNet  MATH  Google Scholar 

  • Heilpern S. (1997). Representation and application of fuzzy numbers, Fuzzy Sets and Systems, 91, 259–268.

    Article  MathSciNet  MATH  Google Scholar 

  • Herencia J. A. (1997). Graded numbers and graded convergence of fuzzy numbers, Fuzzy Sets and Systems, 88, 183–194.

    Article  MathSciNet  MATH  Google Scholar 

  • Hirota K. and Pedrycz W. (1989). Interpretation of results of ranking methods with the aid of probabilistic sets, Fuzzy Sets and Systems, 32, 263–274.

    Article  MathSciNet  MATH  Google Scholar 

  • Höhle U. (1981). Representation theorems for L-fuzzy quantities, Fuzzy Sets and Systems, 5, 83–107.

    Article  MathSciNet  MATH  Google Scholar 

  • Höhle U. (1987). Fuzzy real numbers as Dedekind cuts with respect to a multiple-valued logic, Fuzzy Sets and Systems, 24, 263–278.

    Article  MathSciNet  MATH  Google Scholar 

  • Hong D. H. (1995). A note on t-norm-based addition of fuzzy intervals, Fuzzy Sets and Systems, 75, 73–76.

    Article  MathSciNet  MATH  Google Scholar 

  • Hong D. H. (1996). A note on the convergence of T-sum series of L-R fuzzy numbers, Fuzzy Sets and Systems, 77, 253–254.

    Article  MathSciNet  MATH  Google Scholar 

  • Hong D. H. and Hwang S. Y. (1994a). On the convergence of T-sum of L-R fuzzy numbers, Fuzzy Sets and Systems, 63, 175–180.

    Article  MathSciNet  MATH  Google Scholar 

  • Hong D. H. and Hwang S. Y. (1994b). On the compositional rule of inference under triangular norms, Fuzzy Sets and Systems, 66, 25–38.

    Article  MathSciNet  MATH  Google Scholar 

  • Hong D. H. and Hwang S. Y. (1996). A note on the correlation of fuzzy numbers, Fuzzy Sets and Systems, 79, 401–402.

    Article  MathSciNet  MATH  Google Scholar 

  • Hong D. H. and Hwang S. Y. (1997). A T-sum bound of LR-fuzzy numbers. Fuzzy Sets and Systems, 91, 239–252.

    Article  MathSciNet  MATH  Google Scholar 

  • Hong D. H. and Kim H. (1996). A law of large numbers for fuzzy numbers in a Banach space, Fuzzy Sets and Systems, 77, 349–354.

    Article  MathSciNet  MATH  Google Scholar 

  • Hong D. H. and Kim H. (1998). A note to the sum of fuzzy variables, Fuzzy Sets and Systems, 93, 121-124.

    Google Scholar 

  • Ishibuchi H., Kwon K. and Tanaka H. (1995). A learning algorithm of fuzzy neural networks with triangular fuzzy weights, Fuzzy Sets and Systems, 71, 277–293.

    Article  Google Scholar 

  • Jacas J. and Recasens J. (1993). Fuzzy numbers and equality relations, Proc. IEEE Int. Conf. on Fuzzy Systems, San Francisco, 1298–1301.

    Google Scholar 

  • Jain R. (1976). Tolerance analysis using fuzzy sets, Int. J. Systems Science, 7, 1393–1401.

    Article  MATH  Google Scholar 

  • Jain R. (1977). A procedure for multiple aspect decision-making, Int. J. Systems Science, 8, 1–7.

    Article  MATH  Google Scholar 

  • Jiang H. (1986). The approach to solving simultaneous linear equations that coefficients are fuzzy numbers, J. Nat. Univ. Defence Technology (Chinese), 3, 96–102.

    Google Scholar 

  • Jimenez M. (1996). Ranking fuzzy intervals throgh the comparison of its expected intervals. Int. J. of Uncertainty, Fuzziness and Knowledge-Based Systems, 4, 379–388.

    Article  MathSciNet  MATH  Google Scholar 

  • Jimenez M. and Rivas J. A (1998). Fuzzy number approximation. Int. J. of Uncertainty, Fuzziness and Knowledge-Based Systems, 6, 69–78.

    Article  MathSciNet  MATH  Google Scholar 

  • Juang C.-H., Huang, X. H. and Elton D. J., (1991). Fuzzy information processing by Monte Carlo simulation technique, J. Civil Eng. Systems, 8, 19–25.

    Article  Google Scholar 

  • Kacprzyk J. and Fedrizzi M. (1992). Fuzzy Regression Analysis, Physica-Verlag, Heidelberg.

    Google Scholar 

  • Kaleva O. (1985). On the convergence of fuzzy sets, Fuzzy Sets and Systems, 24, 53–65.

    Article  MathSciNet  Google Scholar 

  • Kaleva O. (1987). Fuzzy differential equations, Fuzzy Sets and Systems, 24, 301–317.

    Article  MathSciNet  MATH  Google Scholar 

  • Kalina M. (1997). Derivatives of fuzzy functions and fuzzy derivatives, Tatra Mount Math. Publ., 12, 27–34.

    MathSciNet  MATH  Google Scholar 

  • Kaufmann A. (1975). Introduction to the Theory of Fuzzy Subsets, Academic Press, New York.

    MATH  Google Scholar 

  • Kaufmann A (1980). La simulation des ensembles flous, CNRS Round Table on Fuzzy Sets, Lyon, France (unpublished proceedings).

    Google Scholar 

  • Kaufmann A. (1981). Hybrid Convolution, a way to combine fuzzy numbers and random numbers, Fuzzy Math. (Huazhong, China), 1(2), 1–12.

    MathSciNet  Google Scholar 

  • Kaufmann A. and Gupta M. M. (1985). Introduction to Fuzzy Arithmetic-Theory and Applications, Van Nostrand Reinhold, New York.

    Google Scholar 

  • Kaufmann A. and Gupta M. M. (1988). Fuzzy Mathematical Models in Engineering and Management Science. North-Holland, Amsterdam.

    Google Scholar 

  • Kawaguchi M. F., and Da-Te T. (1993). A calculation method for solving fuzzy arithmetic equations with triangular norms, Proc. 2d IEEE Int. Conf on Fuzzy Systems (FUZZ-IEEE), San Francisco, 470–476.

    Google Scholar 

  • Kawaguchi M. F. and Da-Te T. (1994). Some algebraic properties of weakly non-interactive fuzzy numbers, Fuzzy Sets and Systems, 68, 281–291.

    Article  MathSciNet  MATH  Google Scholar 

  • Keresztfalvi T. and Kovacs M. (1992). g, p-fuzzification of arithmetic operations, Tatra Mount Math. Publ., 1, 65–71.

    MathSciNet  MATH  Google Scholar 

  • Kerre E. (1982). The use of fuzzy numbers in electrocardiological diagnosis, Approximate Reasoning in Decision Analysis (Gupta M. M. and Sanchez E., eds.), North-Holland, Amsterdam, 277–282.

    Google Scholar 

  • Kerre E. (1987). Fuzzy approach to ECG diagnosis, Encyclopedia of Systems and Control (Singh, M. ed.), Pergamon Press, Oxford, UK, 1405–1407.

    Google Scholar 

  • Kerre E. (1993). Introduction to the Basic Principles of Fuzzy Set Theory and Some of its Applications. Communication & Cognition, Gent, Belgium.

    Google Scholar 

  • Kerre E. and Van Schooten A. (1988). A deeper look on fuzzy numbers from a theoretical as well as from a practical point of view, Fuzzy Logic in Knowledge-Based Systems, Decision and Control (M. M. Gupta, T. Yamakawa, eds.), North-Holland, Amsterdam, 173–196.

    Google Scholar 

  • Kim J. B. (1993), On product-sum of fuzzy complex numbers of an elliptic type, J. Fuzzy Math., 1(3), 611–617.

    MathSciNet  MATH  Google Scholar 

  • Kim K. and Park K. S. (1990). Ranking fuzzy numbers with index of optimum, Fuzzy Sets and Systems, 35, 143–150.

    Article  MathSciNet  Google Scholar 

  • Kim W. J., Ko J. H. and Chung M. J. (1994). Uncertain robot environment modelling using fuzzy numbers, Fuzzy Sets and Systems, 61, 53–62.

    Article  Google Scholar 

  • Klawonn F. and Kruse R. (1993). Equality relations as a basis for fuzzy control, Fuzzy Sets and Systems, 54, 147–156.

    Article  MathSciNet  MATH  Google Scholar 

  • Klement E. P. (1981). Operations on fuzzy sets and fuzzy numbers related to triangular norms, Proc. Ilth IEEE Int. Symp. on Multiple-Valued Logic, Oklahoma City, 218–225.

    Google Scholar 

  • Klement E. P. (1985). Integration of fuzzy valued functions, Revue Roumaine Math. Pures Appl., 30, 375–384.

    MathSciNet  MATH  Google Scholar 

  • Klement E. P. (1987). Strong law of large numbers for random variables with values in the fuzzy real line, IFSA Commun, Math. Chapt., 7–11.

    Google Scholar 

  • Klement E. P., Mesiar R. and Pap E. (1999). Triangular Norms, a book to appear.

    Google Scholar 

  • Klir G. J. (1997). Fuzzy arithmetic with requisite constraints, Fuzzy Sets and Systems, 91, 165–175.

    Article  MathSciNet  MATH  Google Scholar 

  • Klir G. J. (1999). Measures of uncertainty and information, Fundamentals of Fuzzy Sets (Dubois D. and Prade H., eds.), Kluwer Acad. Publ., 1999. This volume.

    Google Scholar 

  • Kolesarova A. (1995). Additions preserving the linearity of fuzzy intervals, Tatra Mount Math. Publ., 6, 75–81.

    MathSciNet  MATH  Google Scholar 

  • Kolesarova A. (1997). Similarity preserving t-norm based additions of fuzzy numbers, Fuzzy Sets and Systems, 91, 215–229.

    Article  MathSciNet  MATH  Google Scholar 

  • Kolesarova A. (1998). Triangular norm-based addition preserving linearity of T-sums of linear fuzzy intervals, Mathware and Soft Computing, 5, 91–98.

    MathSciNet  MATH  Google Scholar 

  • Kolesarova A. and Riecan B. (1993). T∞-fuzzy observables, Int. J. Theor. Physics, 32, 1691–1707.

    Article  MathSciNet  Google Scholar 

  • Kolodziejczyk W. (1986). Orlovsky’s concept of decision-making with a fuzzy relation — Further results. Fuzzy Sets and Systems, 20, 11–20.

    Article  MathSciNet  Google Scholar 

  • Kosheleva O., Cabrera S.D., Gibson G.A. and Koshelev M. (1997). Fast implementations of fuzzy arithmetic operation using fast Fourier transform, Fuzzy Sets and Systems, 91, 269–277.

    Article  MathSciNet  MATH  Google Scholar 

  • Kruse R. (1987). On a software tool for statistics with linguistic data, Fuzzy Sets and Systems, 24, 377–383.

    Article  MathSciNet  Google Scholar 

  • Kruse R. and Meyer K, D (1987). Statistics with Vague Data, Kluwer Academic, Dordrecht, Netherlands.

    Google Scholar 

  • Kwakernaak H. (1978). Fuzzy random variables — Vol. I: Definitions and theorems, Information Sciences, 15, 1–29.

    Article  MathSciNet  MATH  Google Scholar 

  • Kwakernaak H. (1979), Fuzzy random variables —-Part II: Algorithms and examples in the discrete case, Information Sciences, 17, 253–278.

    Article  MathSciNet  MATH  Google Scholar 

  • Kwiesielewicz M. (1998). A note on the fuzzy extension of Saaty’s priority theory, Fuzzy Sets and Systems, 95, 161–173.

    Article  MathSciNet  MATH  Google Scholar 

  • Lai Y. J. and Hwang C. L. (1992). Fuzzy Mathematical Programming-Methods and Applications, Lecture Notes in Economics and Mathematical Systems, vol. 394, Springer-Verlag, Berlin.

    Google Scholar 

  • Lee D. H. and Park D. (1997). An efficient algorithm for fuzzy weighted average, Fuzzy Sets and Systems, 87, 39–45.

    Article  MathSciNet  Google Scholar 

  • Lee K. M., Cho C. H. and Lee-Hwang H. (1994). Ranking fuzzy numbers with satisfaction function, Fuzzy Sets and Systems, 64, 295–311.

    Article  MathSciNet  MATH  Google Scholar 

  • Li RJ. and Lee E. S. (1987). Ranking fuzzy numbers: A comparison, Proc. North-American Fuzzy Inf. Processing Soc. Workshop (NAFIPS’87), Purdue University, West Lafayette, IN, 169–204.

    Google Scholar 

  • Li E. S. and Lee R. J. (1988). Comparison of fuzzy numbers based on the probability measure of fuzzy events, Comp. & Math. with Appl., 15, 887–896.

    MathSciNet  MATH  Google Scholar 

  • Ling C. H. (1965). Representation of associative functions, Publ. Math. Debrecen, 12, 189–212.

    MathSciNet  Google Scholar 

  • Liou T. S. and Wang M. J. J. (1992a). Ranking fuzzy numbers with integral value, Fuzzy Sets and Systems, 50, 247–255.

    Article  MathSciNet  MATH  Google Scholar 

  • Liou T. S. and Wang M. J. J. (1992b). Fuzzy weighted average: An improved algorithm. Fuzzy Sets and Systems, 307–317.

    Google Scholar 

  • Liu X. (1994). On the continuity of fuzzy number valued function, Fuzzy Sets and Systems, 68, 245–247.

    Article  MathSciNet  MATH  Google Scholar 

  • Lootsma F. A. (1985). Performance evaluation of nonlinear optimization methods via pairwise comparison and fuzzy numbers, Math. Prog., 33, 93 et seq.

    Google Scholar 

  • Löwen R. (1980). Convex fuzzy sets, Fuzzy Sets and Systems, 3, 291–310.

    Article  MathSciNet  Google Scholar 

  • Löwen R. (1983a). On (R(L),⊕), Fuzzy Sets and Systems, 10, 203–209.

    Article  MathSciNet  Google Scholar 

  • Lowen R. (1983b). Hyper-spaces of fuzzy sets, Fuzzy Sets and Systems, 9, 287–311.

    Article  MathSciNet  Google Scholar 

  • Lowen R. (1985). The order aspect of the fuzzy real line, Manuscripta Math., 39, 293–309.

    Article  MathSciNet  Google Scholar 

  • Lowen R. (1996). Fuzzy Set Theory, Kluwer, Dordrecht.

    Google Scholar 

  • Mabuchi S (1988). An approach to the comparison of fuzzy subsets with an α-cut dependent index, IEEE Trans. Syst. Man. Cybern., 18, 264–272.

    Article  MathSciNet  Google Scholar 

  • Mandic N. J. and Mamdani E. H. (1980). A linguistic fuzzy calculator. Res. Rep. No. 9, Queen Mary College, University of London, UK.

    Google Scholar 

  • Mares M. (1977a). How to handle fuzzy quantities, Kybernetika (Prague), 13, 23–40.

    MathSciNet  Google Scholar 

  • Mares M. (1977b). On fuzzy quantities with real and integer values, Kyhernetika (Prague), 13, 41–56.

    MathSciNet  MATH  Google Scholar 

  • Mares M. (1993a). Algebraic equivalences over fuzzy quantities, Kyhernetika (Prague), 29(2), 121–132.

    MathSciNet  MATH  Google Scholar 

  • Mares M. (1993b). Remarks on fuzzy quantities with finite support, Kybernetika (Prague), 29(2), 133–143.

    MathSciNet  MATH  Google Scholar 

  • Mares M. (1994), Computation Over Fuzzy Quantities, CRC Press, Boca Raton

    Google Scholar 

  • Mares M. and Mesiar R, (1996). Processing of sources of fuzzy quantities, Proc. IPMU’96, Granada, 359–363.

    Google Scholar 

  • Markov S. M. (1995). On directed interval arithmetics and its applications, J. Universal Computer Science, 1(7), 510–521.

    Google Scholar 

  • Markov S. M. (1996). On the foundations of interval mathematics, Scientific Computing and Validated Numerics (Proc. SCAN-95) (Alefeld G. and Frommer, A., eds.), Akademie-Verlag, Berlin, 307 et seq.

    Google Scholar 

  • Markova A. (1995). Additions of L-R fuzzy numbers, Busefal (IRIT, Université P. Sabatier, Toulouse), 63, 25–29.

    Google Scholar 

  • Markova A. (1997). Idempotents of the T-addition of fuzzy numbers, Tatra Mount Math Publ., 12.

    Google Scholar 

  • Markova A. (1998). T-sum of L-R fuzzy numbers, Fuzzy Sets and Systems, 85, 379–384.

    Article  MathSciNet  Google Scholar 

  • Markova-Stupnanova A. (1997a). A note to the addition of fuzzy intervals based on the continuous Archimedean t-norm, Fuzzy Sets and Systems, 91, 253–258.

    Article  MathSciNet  MATH  Google Scholar 

  • Markova-Stupnanova A. (1997b). Pseudo-convolutions and their idempotents. Proc. 7th Inter. Fuzzy Syst. Assoc. World Cong. (IFSA’97), Prague, June 25–29, 1997, Vol. 1, Academia, 484–487.

    Google Scholar 

  • Markova-Stupnanova A. (1998). A note on recent results on the law of large numbers for fuzzy numbers, BUSEFAL (IRIT, Univ. P. Sabatier, Toulouse), 76, 12–18.

    Google Scholar 

  • Matheron G. (1975). Random Sets and Integral Geometry, John Wiley & Sons, New York.

    MATH  Google Scholar 

  • McCahon C. and Lee E. S. (1990). Comparing fuzzy numbers: the proportion of the optimum method, Int. J. Approximate Reasoning, 4, 159–181.

    Article  MathSciNet  MATH  Google Scholar 

  • McCain R. A. (1983). Fuzzy confidence intervals, Fuzzy Sets and Systems, 10, 281–290.

    Article  MathSciNet  MATH  Google Scholar 

  • Mesiar R. (1993). Fuzzy measurable functions, Fuzzy Sets and Systems, 59, 35–42.

    Article  MathSciNet  MATH  Google Scholar 

  • Mesiar R. (1995). Computation over LR-fuzzy numbers, Proc. CIFT95, Trento, 165–176.

    Google Scholar 

  • Mesiar R. (1996a). LR-fuzzy numbers, Proc. 6th Int. Conf. On Information Processing and Management of Uncertainty in Knowledge-based Systems (IPMU’96), Granada, Spain, 337–342.

    Google Scholar 

  • Mesiar R. (1996b). A note on the T-sum of L-R fuzzy numbers, Fuzzy Sets and Systems, 79, 259–261.

    Article  MathSciNet  MATH  Google Scholar 

  • Mesiar R. (1997a). Shape preserving additions of fuzzy intervals, Fuzzy Sets and Systems, 86, 73–78

    Article  MathSciNet  MATH  Google Scholar 

  • Mesiar R. (1997b). Triangular norm-based additions of fuzzy intervals, Fuzzy Sets and Systems, 91, 231–237.

    Article  MathSciNet  MATH  Google Scholar 

  • Mesiar R. (1998). Approximations of continuous t-norms by strict t-norms with smooth generators, BUSEFAL (IRIT, Université Paul Sabatier, Toulouse), n° 75, 72–79.

    Google Scholar 

  • Miyakawa M., Nakamura K., Ramik J. and Rosenberg I. G. (1993). Joint canonical fuzzy numbers, Fuzzy Sets and Systems, 53, 39–49.

    Article  MathSciNet  MATH  Google Scholar 

  • Miyakoshi M. and Shimbo M. (1984a). A strong law of large numbers for fuzzy-random variables, Fuzzy Sets and Systems, 12, 133–142.

    Article  MathSciNet  MATH  Google Scholar 

  • Miyakoshi M. and Shimbo M. (1984b), An individual ergodic theorem for fuzzy random variables, Fuzzy Sets and Systems, 13, 285–290.

    Article  MathSciNet  MATH  Google Scholar 

  • Mizumoto M. and Tanaka K. (1976a). The four operations of arithmetic on fuzzy numbers, Syst. Comput. Controls, 7(5), 73–81.

    MathSciNet  Google Scholar 

  • Mizumoto M. and Tanaka K. (1976b). Algebraic properties of fuzzy numbers, Proc. Int. Conf, On Cybernetics and Society, Washington, DC, 559–563.

    Google Scholar 

  • Mizumoto M. and Tanaka K. (1976c). Some properties of fuzzy sets of type 2, Inf. Control, 31, 312–340.

    Article  MathSciNet  MATH  Google Scholar 

  • Mizumoto M. and Tanaka K. (1979). Some properties of fuzzy numbers, Advances in Fuzzy Set Theory and Applications (Gupta M. M., Ragade R. K. and Yager R. R., eds.), North-Holland, Amsterdam, 153–165.

    Google Scholar 

  • Moore R. (1966). Interval Analysis, Prentice-Hall, Englewood Cliffs, NJ.

    Google Scholar 

  • Moore R. (1979). Methods and Applications of Interval Analysis, SIAM Studies on Applied Mathematics, Society for Industrial and Applied Mathematics, Philadelphia.

    Google Scholar 

  • Murakami S., Maeda H. and Imamura S. (1989). Fuzzy decison analysis on the development of centralized regional energy control systems. Proc. IFAC Symp. on Fuzzy Information, Knowledge Representation and Decision Processes (Sanchez E. and Gupta M. M, eds.), Pergamon Press, Oxford, 363–368.

    Google Scholar 

  • Murthy C. A, Pal S. K. and Dutta Majumder D. (1985). Correlation bet ween two membership functions, Fuzzy Sets and Systems, 17, 23–38.

    Article  MathSciNet  MATH  Google Scholar 

  • Nahmias S. (1978). Fuzzy variables, Fuzzy Sets and Systems, 1, 97–110.

    Article  MathSciNet  MATH  Google Scholar 

  • Nahmias S. (1979). Fuzzy variables in a random environment, Advances in Fuzzy Set Theory (Gupta M.M., Ragade R. and Yager R. R., eds.), North-Holland, Amsterdam, 165–180.

    Google Scholar 

  • Nakahara Y. (1998). User oriented ranking criteria and application to fuzzy mathematical programming problems, Fuzzy Sets and Systems, 94, 275–286.

    Article  MathSciNet  MATH  Google Scholar 

  • Nakamura K. (1986). Preference relations on a set of fuzzy utilities as a basis for decision-making, Fuzzy Sets and Systems, 20, 147–162.

    Article  MathSciNet  MATH  Google Scholar 

  • Nakamura K. (1990). Canonical fuzzy number of dimension two and fuzzy utility difference for understanding preferential judgements, Information Sciences, 50, 1–22.

    Article  MathSciNet  MATH  Google Scholar 

  • Nanda S. (1989). On sequences of fuzzy numbers, Fuzzy Sets and Systems, 33, 123–126.

    Article  MathSciNet  MATH  Google Scholar 

  • Negoita C. V. (1978). Management Applications of Systems Theory, Birkhauser Verlag, Basel

    Google Scholar 

  • Nguyen H. T. (1978). A note on the extension principle for fuzzy sets, J. Math. Anal Appl., 64, 369–380.

    Article  MathSciNet  MATH  Google Scholar 

  • Nguyen H. T. and Kreinovitch V., Nesterov V. and Nakamura M. (1997). On hardware support for interval computations and for soft computing: theorems, IEEE Trans. on Fuzzy Systems, 5, 108–127.

    Article  Google Scholar 

  • Nguyen H. T., Kreinovitch V. and Wojciechowski P. (1998). Strict Archimedean t-norms and t-co-norms as universal approximators, Int. J. Approximate Reasoning, 18, 239–249.

    Article  MATH  Google Scholar 

  • Oftedal H. (1981). Imprecision of specification of information systems parameters: A study of decision point probabilities, Inform. Syst., 6, 101–109.

    Article  Google Scholar 

  • Orlovsky S.A. (1978). Decision-making with a fuzzy preference relation, Fuzzy Sets and Systems, 1, 155–168.

    Article  MathSciNet  MATH  Google Scholar 

  • Otto K. and Antonsson E. (1991). Trade-off strategies in engineering design, Research in Engineering Design (Springer Verlag), 3, 87–104.

    Article  Google Scholar 

  • Otto K. and Antonsson E. (1994). Design parameter selection in the presence of noise, Research in Engineering Design (Springer Verlag), 6, 234–246.

    Article  Google Scholar 

  • Otto K., Lewis A. D. and Antonsson E. (1993). Approximating α-cuts with the vertex method, Fuzzy Sets and Systems, 55, 43–50.

    Article  MathSciNet  MATH  Google Scholar 

  • Ovchinnikov S. and Migdal M. (1987). On ranking fuzzy sets, Fuzzy Sets and Systems, 24, 113–117.

    Article  MathSciNet  MATH  Google Scholar 

  • Pal N. and Bezdek J.C. (1999). Quantifying different facets of fuzzy uncertainty, Fundamentals of Fuzzy Sets (Dubois D. and Prade H., eds.), Kluwer Acad. Publ., 1999. This volume.

    Google Scholar 

  • Pan Y. and Yuan B. (1997). Bayesian inference of fuzzy probabilities, Int. J. of General Systems, 26(1-2), 73–90.

    Article  MathSciNet  MATH  Google Scholar 

  • Papoulis A. (1965). Probability, Random Variables and Stochastic Processes, McGraw-Hill, New York.

    Google Scholar 

  • Parratt L, G. (1971). Probability and Experimental Errors in Science, Dover, NewYork.

    Google Scholar 

  • Pedrycz W. (1985). On generalized fuzzy relation equations and their applications, J. Math. Anal Appl., 107, 520–536.

    Article  MathSciNet  MATH  Google Scholar 

  • Pedrycz W. (1986). Ranking multiple aspect alternatives — Fuzzy relational approach, Automatica, 22, 251–253.

    Article  MathSciNet  MATH  Google Scholar 

  • Pedrycz W. (1994). Why triangular membership functions?, Fuzzy Sets and Systems, 64, 21–30.

    Article  MathSciNet  Google Scholar 

  • Prade H. (1979). Using fuzzy set theory in a scheduling problem, Fuzzy Sets and Systems, 2, 153–165.

    Article  MathSciNet  MATH  Google Scholar 

  • Prade H. (1980). Operations research with fuzzy data, Fuzzy Sets: Theory and Applications to Policy Analysis and Information Systems (Wang P. P. and Chang S. K., eds.), Plenum Press, New York, 155–170.

    Google Scholar 

  • Prade H. (1982). Modal semantics and fuzzy set theory. In: Fuzzy Set and Possibility Theory. Recent De velopments. (R.R. Yager, ed.), Pergamon Press, New York, 232–246.

    Google Scholar 

  • Prade H. (1984). Lipski’s approach to incomplete information data bases restated and generalized in the setting of Zadeh’s possibility theory, Inf. Syst., 9, 27–42.

    Article  MATH  Google Scholar 

  • Prade H. and Testemaie C. (1984). Generalizing database relational algebra for the treatment of incomplete/uncertain information and vague queries, Information Sciences, 34, 115–143.

    Article  MathSciNet  MATH  Google Scholar 

  • Procyk T. S. and Marndani M. M. (1979). A linguistic self organizing process controller, Automatica, 15, 15–30.

    Article  MATH  Google Scholar 

  • Puncochar J., Drahos M. and Vrba J. (1996). Fuzzy number as a product of geometrical construction, Fuzzy Sets and Systems, 83, 43–50.

    Article  MathSciNet  Google Scholar 

  • Puri M. and Ralescu D. (1981), Différentielle d’une fonction floue, C. R. Acad. Sci. Paris, Ser. I, 293, 237–239.

    MathSciNet  MATH  Google Scholar 

  • Puri M. and Ralescu D. (1983). Differentials of fuzzy functions, J. Math. Anal. Appl., 91, 552–558.

    Article  MathSciNet  MATH  Google Scholar 

  • Puri M. and Ralescu D. (1986), Fuzzy random variables, J. Math. Anal. Appl., 114, 409–422.

    Article  MathSciNet  MATH  Google Scholar 

  • Puri M. L. and Ralescu D. (1991). Convergence theorems for fuzzy martingales, J. Math. Anal Appl., 160, 107–122.

    Article  MathSciNet  MATH  Google Scholar 

  • Quadrat J. P. (1990). Théorèmes asymptotiques en programmation dynamique, C. R. Acad. Sci Paris, Série I, 311, 745–748.

    MathSciNet  MATH  Google Scholar 

  • Ramik J. (1986). Extension principle in fuzzy optimization, Fuzzy Sets and Systems, 19, 29–37.

    Article  MathSciNet  MATH  Google Scholar 

  • Ramik J. and Nakamura K. (1993). Canonical fuzzy numbers of dimension two, Fuzzy Sets and Systems, 54(2), 167–181.

    Article  MathSciNet  Google Scholar 

  • Ramik J. and Rimanek J. (1985). Inequality relation between fuzzy numbers and its use in fuzzy optimization. Fuzzy Sets and Systems, 16, 123–138.

    Article  MathSciNet  MATH  Google Scholar 

  • Ramik J. and Rommelfanger H. (1993). A single-and multi-valued order on fuzzy numbers and its use in linear programming with fuzzy coefficients, Fuzzy Sets and Systems, 57, 203–288.

    Article  MathSciNet  MATH  Google Scholar 

  • Ramik J. and Rommelfanger H. (1996). Fuzzy mathematical progamming based on some new inequality relations, Fuzzy Sets and Systems, 81, 77–87.

    Article  MathSciNet  MATH  Google Scholar 

  • Rao M. B. and Rashed A. (1981). Some comments on fuzzy variables, Fuzzy Sets and Systems, 6, 285–292.

    Article  MathSciNet  MATH  Google Scholar 

  • Requena L, De lgado M. and Verdegay J. L. (1994). Automatic ranking of fuzzy numbers with the criterion of a decision-maker learnt by an artificial neural network, Fuzzy Sets and Systems, 64, 1–21.

    Article  Google Scholar 

  • Requena L, Blanco A., De lgado M. and Verdegay J, L. (1995). A decision personnal index of fuzzy numbers based on neural network, Fuzzy Sets and Systems, 73, 185–201.

    Article  MathSciNet  MATH  Google Scholar 

  • Rockafellar R. T. (1970). Convex Analysis, Princeton Univ. Press, Princeton, NJ.

    Google Scholar 

  • Rodabaugh S. E. (1982). Fuzzy addition in the L-fuzzy real line, Fuzzy Sets and Systems, 8, 39–51.

    Article  MathSciNet  MATH  Google Scholar 

  • Roubens M. (1990). Inequality constraints between fuzzy numbers and their use in mathematical programming, Stochastic vs. Fuzzy Approaches to Multiobjective Mathematical Programming (Slowinski R. and Teghem J., eds.), Kluwer Academic, Dordrecht, Netherlands, 321–330.

    Google Scholar 

  • Roubens M. and Vincke P. (1985). Preference Modelling, Springer Verlag, Berlin.

    Google Scholar 

  • Roubens M. and Vincke P. (1988). Fuzzy possibility graphs and their application to ranking fuzzy numbers, Non-Conventional Preference Relations in Decision Making (Kacprzyk J. and. Roubens M., eds.), 119–128.

    Google Scholar 

  • Saade J. J. and Schwarzlander H. (1992). Ordering fuzzy sets over the real line: An approach besed on decision making under uncertainty, Fuzzy Sets and Systems, 50, 237–246.

    Article  MathSciNet  Google Scholar 

  • Saaty T. L. (1980). The Analytic Hierarchy Process: Planning, Priority Setting, Resource Allocation, McGraw-Hill, New York.

    Google Scholar 

  • Sage A. P. (1981). Sensitivity analysis in systems for planning and decision support, J. Franklin Inst., 312, 265–291.

    Article  MathSciNet  MATH  Google Scholar 

  • Sakawa M. (1993). Fuzzy Sets and Interactive Multiobjective Optimization, Plenum Press, New York.

    MATH  Google Scholar 

  • Salakhutdinov R.R., Salakhutdinov R.Z. (1998), The law of large numbers and T-stability fuzzy numbers, BUSEFAL (IRIT, Univ. P. Sabatier), 74, 64–67.

    Google Scholar 

  • Sanchez E. (1984). Solution of fuzzy equations with extended operations, Fuzzy Sets and Systems, 12, 237–248.

    Article  MathSciNet  MATH  Google Scholar 

  • Sanchez E. (1996). Truth-qualification and fuzzy relations in natural languages, application to medical diagnosis, Fuzzy Sets and Systems, 84, 155–167.

    Article  MathSciNet  MATH  Google Scholar 

  • Sarna M. (1989). Fuzzy relations on fuzzy and non fuzzy numbers — Fast computation formulas, Fuzzy Sets and Systems, 29, 155–163.

    Article  MathSciNet  MATH  Google Scholar 

  • Sarna M. (1998). Fuzzy relations on fuzzy and non fuzzy numbers; fast computation formulas: II. Fuzzy Sets and Systems, 93, 63–74.

    Article  MathSciNet  MATH  Google Scholar 

  • Schweizer B. (1975). Multiplications on the space of probability distribution functions, Aeq. Math., 12, 156–183.

    Article  MathSciNet  MATH  Google Scholar 

  • Schweizer B. and Sklar A. (1963). Associative functions and abstract semi-groups, Publ. Math. Debrecen, 10, 69–81.

    MathSciNet  Google Scholar 

  • Schweizer B. and Sklar A. (1983), Probabilistic Metric Spaces, North Holland, New York.

    Google Scholar 

  • Scott M. and Antonsson E. (1995). Aggregation functions for engineering design trade-offs, Proc. of the 9th Int. Conf on Design Theory and Methodology, Vol. 2, 389–396.

    Google Scholar 

  • Sebastian H.-J. and Antonsson E. (eds.) (1996). Fuzzy Sets in Engineering Design and Configuration, Kluwer Academic, Dordrecht, The Netherlands.

    Google Scholar 

  • Shafer G. (1976). A Mathematical Theory of Evidence, Princeton University Press, Princeton.

    Google Scholar 

  • Sinha D. (1990). A general theory of fuzzy arithmetic, Fuzzy Sets and Systems, 36, 339–364.

    Article  MathSciNet  MATH  Google Scholar 

  • Slowinski R (1998). Fuzzy sets in decision analysis operations research and statistics, The Handbooks of Fuzzy Sets Series, Kluwer, Boston, USA.

    Google Scholar 

  • Schmeidler, D. (1989)Subjective probability and expected utility without additivity. Econometrica, 57, 571–587.

    Article  MathSciNet  MATH  Google Scholar 

  • Schmucker K. J. (1984). Fuzzy Sets, Natural Language Conputations and Risk Analysis, Computer Science Press, Rockville, MD.

    Google Scholar 

  • Sinha D., Dougherty, E.R. (1995). A general axiomatic theory of intrinsically fuzzy mathematical morphologies, IEEE Trans, on Fuzzy Systems, 3, 389–403.

    Article  Google Scholar 

  • Slowinski R. (Ed.) (1998). Fuzzy Sets in Decision Analysis, Operations Research and Statistics. The Handbooks of Fuzzy Sets Series (D. Dubois, H. Prade, eds,), Kluwer Acad. Publ., Boston.

    MATH  Google Scholar 

  • Song Q. and Chissom B, S. (1993a). Fuzzy time series and its models, Fuzzy Sets and Systems, 54, 269–277.

    Article  MathSciNet  MATH  Google Scholar 

  • Song Q. and Chissom R. S. (1993b). Forecasting enrollments with fuzzy time series: Part I, Fuzzy Sets and Systems, 54, 1–9.

    Article  MathSciNet  Google Scholar 

  • Song Q, and Chissom B. S. (1994). Forecasting enrollments with fuzzy time series: Part II, Fuzzy Sets and Systems, 62, 1–8.

    Article  Google Scholar 

  • Song Q., Leland R. L. and Chissom B. S. (1995). A new fuzzy time-series model of fuzzy number observations, Fuzzy Sets and Systems, 73, 341–348.

    Article  MathSciNet  MATH  Google Scholar 

  • Stanford R. E. (1982). The set of limiting distributions for a Markov chain with fuzzy transition probabilities, Fuzzy Sets and Systems, 7, 71–78.

    Article  MathSciNet  MATH  Google Scholar 

  • Stein W. E. (1983). A note on convexity and fuzzy random variables, BUSEFAL (IRIT, Université P. Sabatier, Toulouse), 14, 43–46.

    MATH  Google Scholar 

  • Stein W. E. and Talati K. (1981). Convex fuzzy random variables, Fuzzy Sets and Systems, 6, 271–283.

    Article  MathSciNet  MATH  Google Scholar 

  • Steyaert H., Van Parys F., Baekeland R. and Kerre E. (1995). Implementation of piecewise linear fuzzy quantities, Int. J. Intelligent Systems, 10, 1049–1059.

    Article  Google Scholar 

  • Stojakovic M. (1994). Fuzzy valued measure. Fuzzy Sets and Systems, 65, 95–104.

    Article  MathSciNet  MATH  Google Scholar 

  • Stojakovic M. and Stojakovic Z. (1996). Additions and series of fuzzy sets, Fuzzy Sets and Systems, 83, 341–346.

    Article  MathSciNet  MATH  Google Scholar 

  • Subrahmanyam P. V. and Sudarsanam S. K. (1994). On some fuzzy functional equations, Fuzzy Sets and Systems, 64, 333–338.

    Article  MathSciNet  MATH  Google Scholar 

  • Tamura N. and Horiuchi K. (1993). VSOP fuzzy numbers and fuzzy comparison relations, Proc. FUZZ-IEEE, San Francisco, 1287–1292.

    Google Scholar 

  • Tanaka H. and Asai K. (1984a). Fuzzy linear programming with fuzzy numbers, Fuzzy Sets and Systems, 13, 1–10.

    Article  MathSciNet  MATH  Google Scholar 

  • Tanaka H. and Asai K. (1984b). Fuzzy solution in fuzzy linear programming problems, IEEE Trans. Syst. Man. Cybern., 14, 325–328.

    Article  MATH  Google Scholar 

  • Tanaka H. and Diamond P. (1998). Fuzzy regression analysis, Fuzzy Sets in Decision Analysis, Operations Research and Statistics (Slowinski, R., ed.), The Handbook of Fuzzy Sets Series, Kluwer Academic Publ., Dordrecht, 349–390.

    Google Scholar 

  • Tong R. M. and Bonissone P. P. (1980). A linguistic approach to decision making with fuzzy sets, IEEE Trans. Syst. Man. Cybern., 10, 716–723.

    Article  MathSciNet  Google Scholar 

  • Triesch E. (1993). On the convergence of product-sum series of L-R fuzzy numbers, Fuzzy Sets and Systems, 53, 189–192.

    Article  MathSciNet  MATH  Google Scholar 

  • Tseng T. Y. and Klein C. (1988). A survey and comparative study of ranking procedures in fuzzy decision making. Working Paper n° 8812101, Dept. of Industrial Engineering, University of Missouri-Columbia, USA.

    Google Scholar 

  • Tseng T. Y. and Klein C. (1989). New algorithm for the ranking procedure in fuzzy decision-making, IEEE Trans. Syst. Man. Cybern., 19, 1289–1296.

    Article  MathSciNet  Google Scholar 

  • Tsukamoto Y., Nikiforuk P. N. and Gupta M. M. (1981). On the comparison of fuzzy sets using fuzzy chopping, Proc. 8th Triennial World Congress IFAC, Vol. 5, Pergamon Press, Oxford, 46–52.

    Google Scholar 

  • Tsang E. (1993). Foundations of Constraint Satisfaction, Academic Press, New York.

    Google Scholar 

  • Umano M. (1982). Fredom-0: A fuzzy data base system, Fuzzy Information and Decision Processes (Gupta M. M. and Sanchez E., eds.), North-Holland, 339–347.

    Google Scholar 

  • Van Laatroven P. J. M. and Pedrycz W. (1983). A fuzzy extension of Saaty’s priority theory, Fuzzy Sets and Systems, 11, 229–241.

    Article  MathSciNet  Google Scholar 

  • Van Leekwijk W. and Kerre E. (1998). Defuzzification: criteria and classification. University of Gent, Belgium. To appear in Fuzzy Sets and Systems.

    Google Scholar 

  • Viertl R. (1996). Statistical Methods for Non Precise Data.CRC Press, Boca Raton, FL.

    Google Scholar 

  • Vrba J. (1992). A note on inverses in arithmetics with fuzzy numbers, Fuzzy Sets and Systems, 50, 267–278.

    Article  MathSciNet  Google Scholar 

  • Wagenknecht M. and Hartmann K. (1983). On fuzzy rank-ordering in poly-optimization, Fuzzy Sets and Systems, 11, 253–264.

    Article  MathSciNet  MATH  Google Scholar 

  • Wang P. Z. (1983). From the fuzzy statistics to the falling random subsets, Advances in Fuzzy Sets, Possibility Theory and Applications (Wang P. P., ed.), Plenum Press, New York, 81–96.

    Chapter  Google Scholar 

  • Wang X. (1997). A comparative study of the ranking methods for fuzzy quantities, PhD. Thesis, University of Gent, Belgium.

    Google Scholar 

  • Wang X. and Ha M. (1994), Solving a system of fuzzy linear equations, Fuzzy Optimization: Recent Advances (Delgado M., Kacprzyk J., Verdegay J. L. and Vila M. A., eds.), Physica-Verlag, Heidelberg, Germany, 102–108.

    Google Scholar 

  • Wang X. and Kerre E. (1996). On the classification and the dependencies of the ordering methods, Fuzzy Logic Foundations and Industrial Applications (Rua D., ed.), Kluwer Academic Publishers, Dordrecht, The Netherlands, 73–88.

    Chapter  Google Scholar 

  • Wang X. and Kerre E. (1998). Reasonable properties for the ordering of fuzzy quantities, Fuzzy Sets and Systems, to appear.

    Google Scholar 

  • Wang X., Kerre E. and Da Ruan. (1995a). Consistency and weights of judgment matrix in fuzzy AHP, Int. J. of Uncertainty, Fuzziness and Knowledge-based Systems, 3, 35–46.

    Article  MathSciNet  MATH  Google Scholar 

  • Wang X., Kerre E. and Da Ruan. (1995b). Transitivity of fuzzy orderings based on pairwise comparisons, Int. J. Fuzzy Math., 3, 455–463.

    MathSciNet  MATH  Google Scholar 

  • Wang X. and Da Ruan. (1995). On the transitivity of fuzzy preference relations in ranking fuzzy numbers, Fuzzy Set Theory and Advanced Mathematical Applications (Rua D., ed.), Kluwer Academic Publishers, Dordrecht, The Netherlands, 155–173.

    Chapter  Google Scholar 

  • Wang Z. and Klir G. J. (1992), Fuzzy Measure Theory, Plenum Press, New York.

    MATH  Google Scholar 

  • Wasowski J. (1997). On solutions to fuzzy equations, Control and Cybern., 26, 653–658.

    MathSciNet  MATH  Google Scholar 

  • Watson S. R., Weiss J. J. and Donnell M. (1979). Fuzzy decision analysis, IEEE Trans, Syst. Man. Cybern., 9, 1–9.

    Article  Google Scholar 

  • Williamson R. C. (1991). The law of large numbers for fuzzy variables under a general triangular norm extension principle, Fuzzy Sets and Systems, 41, 55–81.

    Article  MathSciNet  MATH  Google Scholar 

  • Willmott R. (1981). Mean measures of containment and equality between fuzzy sets, Proc. 11th Int. Symp. on Multiple Valued Logic, Oklahoma City, 183–190.

    Google Scholar 

  • Woods K., Otto K. and Antonsson E. (1992). Engineering design calculations under uncertainty, Fuzzy Sets and Systems, 52, 1-20

    Google Scholar 

  • Wu C. and Qiu J. (1998). Some remarks for fuzzy complex analysis, Fuzzy Sets and Systems, to appear.

    Google Scholar 

  • Yager R. R. (1979a). A note on probabilities of fuzzy events, Information Sciences, 18, 113–129.

    Article  MathSciNet  MATH  Google Scholar 

  • Yager R. R. (1979b). On solving fuzzy mathematical relationships, Inf Control, 41, 29–55.

    Article  MathSciNet  MATH  Google Scholar 

  • Yager R. R. (1979c). Ranking fuzzy subsets over the unit interval, Proc. 17th IEEE Int. Confon Decision and Control, San Diego, CA, 1535–1437.

    Google Scholar 

  • Yager R. R. (1980a). On the lack of inverses in fuzzy arithmetic, Fuzzy Sets and Systems, 4, 73–82.

    Article  MathSciNet  MATH  Google Scholar 

  • Yager R. R. (1980b). On choosing between fuzzy subsets, Kybernetes, 9, 151–154.

    Article  MATH  Google Scholar 

  • Yager R. R. (1981). A procedure for ordering fuzzy subsets of the unit interval, Information Sciences, 24, 143–161.

    Article  MathSciNet  MATH  Google Scholar 

  • Yager R. R. (1982). Measuring tranquility and anxiety in decision-making: An application of fuzzy sets. Int. J. General Systems, 9, 249–260.

    Article  MathSciNet  Google Scholar 

  • Yager R. R. (1986). A characterization of the extension principle, Fuzzy Sets and Systems, 18, 205–219.

    Article  MathSciNet  MATH  Google Scholar 

  • Yager R. R. and Filev D. (1993). On the issue of defuzzification and selection based on a fuzzy set, Fuzzy Sets and Systems, 55, 255–271.

    Article  MathSciNet  MATH  Google Scholar 

  • Yager R. R. and Filev D. (1994). Essentials of Fuzzy Modeling and Control, Wiley, New York.

    Google Scholar 

  • Yager R. R. and Kelman (1996). A. fusion of fuzzy information with consideration of compatibility, partial aggregation and reinforcement, Int. J. Approximate Reasoning, 15, 93–122.

    Article  MathSciNet  MATH  Google Scholar 

  • Yang HQ. Hua Y. and Jones J. D. (1993). Calculating functions of fuzzy numbers, Fuzzy Sets and Systems, 55, 273–283.

    Article  MathSciNet  Google Scholar 

  • Yoon K. P. (1996). A probabilistic approach to rank complex fuzzy numbers, Fuzzy Sets and Systems, 80, 167–176.

    Article  MathSciNet  Google Scholar 

  • Young R. C. (1931). The algebra of many-valued quantities, Math. Ann., 104, 260–290.

    Article  MathSciNet  Google Scholar 

  • Yu C. (1993). Correlation of fuzzy numbers, Fuzzy Sets and Systems, 55, 303–307.

    Article  MathSciNet  MATH  Google Scholar 

  • Yuan Y. (1991). Criteria for evaluating fuzzy ranking methods, Fuzzy Sets and Systems, 44, 139–157.

    Article  MathSciNet  Google Scholar 

  • Zadeh L. A. (1965). Fuzzy sets, Inf. Control, 8, 338–353.

    Article  MathSciNet  MATH  Google Scholar 

  • Zadeh L. A. (1975a). The concept of a linguistic variable and its application to approximate reasoning, Information Sciences, Part I: 8, 199-249; Part II: 8, 301-357; Part III: 9, 43–80.

    Article  MathSciNet  MATH  Google Scholar 

  • Zadeh L. A. (1975b). Calculus of fuzzy restrictions, Fuzzy Sets and Their Applications to Cognitive and De cision Processes (Zadeh L. A., Fu K. S., Shimura M. and Tanuka K., eds.), Academic Press, New York, 1–39.

    Google Scholar 

  • Zadeh L. A. (1978). Fuzzy sets as a basis for a theory of possibility, Fuzzy Sets and Systems, 1, 3–28.

    Article  MathSciNet  MATH  Google Scholar 

  • Zadeh L. A. (1979). A theory of approximate reasoning, Machine Intelligence, Vol. 9 (Hayes J. E., Michie D. and Mikulich L. I., eds.), John Wiley & Sons, New York, 149–194.

    Google Scholar 

  • Zadeh L. A. (1983), A computational approach to linguistic quantifiers in natural language, Comp. Math. Appl., 9, 149–184.

    Google Scholar 

  • Zadeh L. A. (1996). Fuzzy logic-computing with words, IEEE Trans. Fuzzy Systems, 4, 103–111.

    Article  Google Scholar 

  • Zhang G. Q. (1993). The convergence of a sequence of fuzzy integrals of fuzzy number-valued functions on the fuzzy set, Fuzzy Sets and Systems, 59, 43–57.

    Article  MathSciNet  MATH  Google Scholar 

  • Zhang D. and Wang Z. (1993). Fuzzy integrals of fuzzy-valued functions, Fuzzy Sets and Systems, 54, 63–67.

    Article  MathSciNet  MATH  Google Scholar 

  • Zhao R, and Govind R. (1991a). Algebraic characteristics of extended fuzzy numbers, Information Sciences, 54, 103–130.

    Article  MathSciNet  MATH  Google Scholar 

  • Zhao R. and Govind R. (1991b). Solutions of algebraic equations involving generalized fuzzy numbers, Information Sciences, 56, 199–243.

    Article  MathSciNet  MATH  Google Scholar 

  • Zhao R. and Govind R. (1991c). Defuzzification of fuzzy intervals, Fuzzy Sets and Systems, 43, 45–56.

    Article  MathSciNet  MATH  Google Scholar 

  • Zhu Q. and Lee E. S. (1992). Comparison and ranking of fuzzy numbers, Fuzzy Regression Analysis (Kacprzyk J. and Fedrizzi M., eds.), Omnitech Press, Warsaw, Poland, 21–44.

    Google Scholar 

  • Zimmermann H. J. (Ed.) (1999), Practical Applications of Fuzzy Technologies, The Handbooks of Fuzzy Sets Series (D. Dubois, Prade H., eds.), Kluwer Academic Publ., New York.

    Google Scholar 

Download references

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2000 Springer Science+Business Media New York

About this chapter

Cite this chapter

Dubois, D., Kerre, E., Mesiar, R., Prade, H. (2000). Fuzzy Interval Analysis. In: Dubois, D., Prade, H. (eds) Fundamentals of Fuzzy Sets. The Handbooks of Fuzzy Sets Series, vol 7. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-4429-6_11

Download citation

  • DOI: https://doi.org/10.1007/978-1-4615-4429-6_11

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4613-6994-3

  • Online ISBN: 978-1-4615-4429-6

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics