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Fuzzy systems

  • Robert Fullér
Part of the Advances in Soft Computing book series (AINSC, volume 2)

Abstract

Fuzzy sets were introduced by Zadeh [235] as a means of representing and manipulating data that was not precise, but rather fuzzy.

Keywords

Membership Function Fuzzy Number Fuzzy System Fuzzy Logic Controller Triangular Fuzzy Number 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Bibliography

  1. 1.
    K.J. Arrow, Social Choice and Individual Values (John Wiley & Sons, New York, 1951).MATHGoogle Scholar
  2. 2.
    R.A. Bellman and L.A. Zadeh, Decision-making in a fuzzy environment, Management Sciences, Ser. B 17 (1970) 141–164.MathSciNetGoogle Scholar
  3. 3.
    J. F. Brule, Fuzzy systems - a tutorial, (http://www.austinlinks.com/Fuzzy/tutorial.html, 1985).Google Scholar
  4. 4.
    D. Butnariu and E.P. Klement, Triangular Norm-Based Measures and Games with Fuzzy Coalitions (Kluwer, Dordrecht, 1993).MATHGoogle Scholar
  5. 5.
    D. Butnariu, E.P. Klement and S. Zafrany, On triangular norm-based propositional fuzzy logics, Fuzzy Sets and Systems, 69 (1995) 241–255.MathSciNetMATHGoogle Scholar
  6. 6.
    E. Canestrelli and S. Giove, Optimizing a quadratic function with fuzzy linear coefficients, Control and Cybernetics, 20 (1991) 25–36.MathSciNetMATHGoogle Scholar
  7. 7.
    E. Canestrelli and S. Giove, Bidimensional approach to fuzzy linear goal programming, in: M. Delgado, J. Kacprzyk, J.L. Verdegay and M.A. Vila eds., Fuzzy Optimization (Physical Verlag, Heildelberg, 1994) 234–245.Google Scholar
  8. 8.
    E. Canestrelli, S. Giove and R. Fullér, Sensitivity analysis in possibilistic quadratic programming, Fuzzy Sets and Systems, 82 (1996) 51–56.MathSciNetMATHGoogle Scholar
  9. 9.
    B. Cao, New model with T-fuzzy variations in linear programming, Fuzzy Sets and Systems, 78 (1996) 289–292.MathSciNetMATHGoogle Scholar
  10. 10.
    C. Carlsson, A. Törn and M. Zeleny eds., Multiple Criteria Decision Making: Selected Case Studies, McGraw Hill, New York 1981.Google Scholar
  11. 11.
    C. Carlsson, Tackling an MCDM-problem with the help of some results from fuzzy sets theory, European Journal of Operational Research, 3 (1982) 270–281.Google Scholar
  12. 12.
    C. Carlsson, An approach to handle fuzzy problem structures, Cybernet. and Systems, 14 (1983) 33–54.MathSciNetMATHGoogle Scholar
  13. 13.
    C. Carlsson, On the relevance of fuzzy sets in management science methodology, TIMS/Studies in the Management Sciences, 20 (1984) 11–28.MathSciNetGoogle Scholar
  14. 14.
    C. Carlsson, Fuzzy multiple criteria for decision support systems, in: M.M. Gupta, A. Kandel and J.B. Kiszka eds., Approximate Reasoning in Expert Systems (North-Holland, Amsterdam, 1985) 48–60.Google Scholar
  15. 15.
    C. Carlsson, and P.Korhonen, A parametric approach to fuzzy linear programming, Fuzzy Sets and Systems, 20 (1986) 17–30.MathSciNetMATHGoogle Scholar
  16. 16.
    C. Carlsson, Approximate Reasoning for solving fuzzy MCDM problems, Cybernetics and Systems: An International Journal 18 (1987) 35–48.MathSciNetGoogle Scholar
  17. 17.
    C. Carlsson, Approximate reasoning through fuzzy MCDM-models, Operation Research’87 (North-Holland, Amsterdam, 1988) 817–828.Google Scholar
  18. 18.
    C. Carlsson, On interdependent fuzzy multiple criteria, in: R. Trappl ed., Cybernetics and Systems’90 (World Scientific, Singapore, 1990) 139–146.Google Scholar
  19. 19.
    C. Carlsson, On optimization with interdependent multiple criteria, in: R. Lo-wen and M. Roubens eds., Proc. of Fourth IFSA Congress, Vol. Computer, Management and Systems Science, Brussels, 1991 19–22.Google Scholar
  20. 20.
    C. Carlsson, On optimization with interdependent multiple criteria, in: R. Lo-wen and M. Roubens eds., Fuzzy Logic: State of the Art, Kluwer Academic Publishers, Dordrecht, 1992 415–422.Google Scholar
  21. 21.
    C. Carlsson, Cognitive Maps and Hyperknowledge. A Blueprint for Active Decision Support Systems, in: Cognitive Maps and Strategic Thinking, C. Carlsson ed. May 1995, Abo, Finland, (Meddelanden Fran Ekonomisk-Statsvetenskapliga Fakulteten Vid Abo Akademi, IAMSR, Ser. A: 442) 27–59.Google Scholar
  22. 22.
    C. Carlsson, D. Ehrenberg, P. Eklund, M. Fedrizzi, P. Gustafsson, P. Lindholm, G. Merkuryeva, T. Riissanen and A. Ventre, Consensus in distributed soft environments, European Journal of Operational Research, 61 (1992) 165–185Google Scholar
  23. 23.
    C. Carlsson and R. Fullér, Fuzzy if-then rules for modeling interdependencies in FMOP problems, in: Proceedings of EUFIT’94 Conference, September 20–23, 1994 Aachen, Germany (Verlag der Augustinus Buchhandlung, Aachen, 1994) 1504–1508.Google Scholar
  24. 24.
    C. Carlsson and R. Fullér, Interdependence in fuzzy multiple objective programming, Fuzzy Sets and Systems, 65 (1994) 19–29.MathSciNetGoogle Scholar
  25. 25.
    C. Carlsson and R. Fullér, Fuzzy reasoning for solving fuzzy multiple objective linear programs, in: R. Trappl ed., Cybernetics and Systems ‘84, Proceedings of the Twelfth European Meeting on Cybernetics and Systems Research (World Scientific Publisher, London, 1994) 295–301.Google Scholar
  26. 26.
    C. Carlsson and R. Fullér, Multiple Criteria Decision Making: The Case for Interdependence, Computers €9 Operations Research 22 (1995) 251–260.MATHGoogle Scholar
  27. 27.
    C. Carlsson and R. Fullér, On linear interdependences in MOP, in: Proceedings of CIFT’95 Workshop, June 8–10, 1995, Trento, Italy, University of Trento, 1995 48–52.Google Scholar
  28. 28.
    C. Carlsson and R. Fullér, Active DSS and approximate reasoning, in: Proceedings of EUFIT’95 Conference, August 28–31, 1995, Aachen, Germany, Verlag Mainz, Aachen, 1995 1209–1215.Google Scholar
  29. 29.
    C. Carlsson and R. Fullér, On fuzzy screening system, in: Proceedings of the Third European Congress on Intelligent Techniques and Soft Computing (EUFIT’95), August 28–31, 1995 Aachen, Germany, Verlag Mainz, Aachen, [ISBN 3–930911–67–1], 1995 1261 – 1264.Google Scholar
  30. 30.
    C. Carlsson and R. Fullér, Fuzzy multiple criteria decision making: Recent developments, Fuzzy Sets and Systems, 78 (1996) 139–153.MathSciNetMATHGoogle Scholar
  31. 31.
    C. Carlsson and R. Fullér, Additive interdependences in MOP, in: M.Brännback and M.Kuula eds., Proceedings of the First Finnish Noon-to-noon seminar on Decision Analysis, Abo, December 11–12, 1995, Meddelanden Fran EkonomiskStatsvetenskapliga Fakulteten vid Abo Akademi, Ser: A:459, Abo Akademis tryckeri, Abo, 1996 77–92.Google Scholar
  32. 32.
    C. Carlsson and R. Fullér, Compound interdependences in MOP, in: Proceedings of the Fourth European Congress on Intelligent Techniques and Soft Computing (EUFIT’96), September 2–5, 1996, Aachen, Germany, Verlag Mainz, Aachen, 1996 1317–1322.Google Scholar
  33. 33.
    C. Carlsson and R. Fullér, Problem-solving with multiple interdependent criteria: Better solutions to complex problems, in: D. Ruan, P. D’hondt, P. Govaerts and E.E. Kerre eds., Proceedings of the Second International FLINS Workshop on Intelligent Systems and Soft Computing for Nuclear Science and Industry, September 25–27, 1996, Mol, Belgium, World Scientific Publisher, 1996 89–97.Google Scholar
  34. 34.
    C. Carlsson and R. Fullér, Adaptive Fuzzy Cognitive Maps for Hyperknowledge Representation in Strategy Formation Process, in: Proceedings of International Panel Conference on Soft and Intelligent Computing, Budapest, October 7–10, 1996, Technical University of Budapest, 1996 43–50.Google Scholar
  35. 35.
    C. Carlsson and R. Fullér, A neuro-fuzzy system for portfolio evaluation, in: R.Trappl ed., Cybernetics and Systems ‘86, Proceedings of the Thirteenth European Meeting on Cybernetics and Systems Research, Vienna, April 9–12, 1996, Austrian Society for Cybernetic Studies, Vienna, 1996 296–299.Google Scholar
  36. 36.
    C. Carlsson, R. Fuller and S. Fullér, Possibility and necessity in weighted aggregation, in: R.R. Yager and J. Kacprzyk eds., The ordered weighted averaging operators: Theory, Methodology, and Applications, Kluwer Academic Publishers, Boston, 1997 18–28.Google Scholar
  37. 37.
    C. Carlsson, R. Fuller and S. Fullér, OWA operators for doctoral student selection problem, in: R.R. Yager and J. Kacprzyk eds., The ordered weighted averaging operators: Theory, Methodology, and Applications, Kluwer Academic Publishers, Boston, 1997 167–178.Google Scholar
  38. 38.
    C. Carlsson and R. Fullér, Problem solving with multiple interdependent criteria, in: J. Kacprzyk, H. Nurmi and M. Fedrizzi eds., Consensus under Fuzziness, The Kluwer International Series in Intelligent Technologies, Vol. 10, Kluwer Academic Publishers, Boston, 1997. 231–246.Google Scholar
  39. 39.
    C. Carlsson and R. Fullér, OWA operators for decision support, in: Proceedings of the Fifth European Congress on Intelligent Techniques and Soft Computing (EUFIT’97), September 8–11, 1997, Aachen, Germany, Verlag Mainz, Aachen, Vol. II, 1997 1539–1544.Google Scholar
  40. 40.
    C. Carlsson and R. Fullér, Soft computing techniques for portfolio evaluation, in: A. Zempléni ed., Statistics at Universities: Its Impact for Society, Tempus (No. 9521) Workshop, Budapest, May 22–23, 1997, Eötvös University Press, Budapest, Hungary, 1997 47–54.Google Scholar
  41. 41.
    C. Carlsson and R. Fullér, A novel approach to linguistic importance weighted aggregations, in: C. Carlsson and I.Eriksson eds., Global ê? Multiple Criteria Optimization and Information Systems Quality, Abo Akademis tryckeri, Abo, 1998 143–153.Google Scholar
  42. 42.
    C. Carlsson and R. Fuller, A new look at linguistic importance weighted aggregations, Cybernetics and Systems ‘88, Proceedings of the Fourteenth European Meeting on Cybernetics and Systems Research, Austrian Society for Cybernetic Studies, Vienna, 1998 169–174Google Scholar
  43. 43.
    C. Carlsson and R. Fullér, Benchmarking in linguistic importance weighted aggregations, Fuzzy Sets and Systems? 1999 (to appear).Google Scholar
  44. 44.
    C. Carlsson and R. Fullér, Optimization with linguistic values, TUCS Technical Reports, Turku Centre for Computer Science, No. 157/1998. [ISBN 952–12–0138X, ISSN 1239–1891].Google Scholar
  45. 45.
    C. Carlsson and R. Fullér, Multiobjective optimization with linguistic variables, in: Proceedings of the Sixth European Congress on Intelligent Techniques and Soft Computing (EUFIT’98), Aachen, September 7–10, 1998, Verlag Mainz, Aachen, [ISBN 3–89653–500–5], Vol. II, 1998 1038–1042.Google Scholar
  46. 46.
    C. Carlsson and R. Fullér, Optimization under fuzzy if-then rules, Fuzzy Sets and Systems? 1999, (to appear).Google Scholar
  47. 47.
    C. Carlsson and R. Fullér, On mean value and variance of fuzzy numbers, Research Reports, Institute for Advanced Management Systems Research, Abo Akademi University, July, 1999, No. 1999/8. [ISBN 952–12–0500–8, ISSN 12359505]Google Scholar
  48. 48.
    C. Carlsson and R. Fullér, On mean value and variance of fuzzy numbers, Fuzzy Sets and Systems? (submitted).Google Scholar
  49. 49.
    C. Carlsson and P. Walden, Active DSS and Hyperknowledge: Creating Strategic Visions, in: Proceedings of EUFIT’95 Conference, August 28–31, 1995, Aachen, Germany, (Verlag Mainz, Aachen, 1995) 1216–1222.Google Scholar
  50. 50.
    J.L. Castro, Fuzzy logic contollers are universal approximators, IEEE Transactions on Syst. Man Cybernet., 25 (1995) 629–635.Google Scholar
  51. 51.
    S.M. Chen, A weighted fuzzy reasoning akgorithm for medical diagnosis, Decision Support Systems, 11 (1994) 37–43.Google Scholar
  52. 52.
    E. Cox, The Fuzzy system Handbook. A Practitioner’s Guide to Building, Using, and Maintaining Fuzzy Systems (Academic Press, New York, 1994).Google Scholar
  53. 53.
    M. Delgado, E. Trillas, J.L. Verdegay and M.A. Vila, The generalized “modus ponens” with linguistic labels, in: Proceedings of the Second International Conference on Fuzzy Logics andd Neural Network, IIzuka, Japan, 1990 725–729.Google Scholar
  54. 54.
    M. Delgado, J. Kacprzyk, J.L. Verdegay and M.A. Vila eds., Fuzzy Optimization (Physical Verlag, Heildelberg, 1994).MATHGoogle Scholar
  55. 55.
    J. Dombi, A general class of fuzzy operators, the DeMorgan class of fuzzy operators and fuziness measures induced by fuzzy operators, Fuzzy Sets and Systems, 8 (1982) 149–163.MathSciNetMATHGoogle Scholar
  56. 56.
    J. Dombi, Membership function as an evaluation, Fuzzy Sets and Systems, 35 (1990) 1–21.MathSciNetMATHGoogle Scholar
  57. 57.
    D. Driankov, H. Hellendoorn and M. Reinfrank, An Introduction to Fuzzy Control (Springer Verlag, Berlin, 1993).MATHGoogle Scholar
  58. 58.
    D. Dubois, R. Martin-Clouaire and H. Prade, Practical computation in fuzzy logic, in: M.M. Gupta and T. Yamakawa eds., Fuzzy Computing (Elsevier Science Publishing, Amsterdam, 1988) 11–34.Google Scholar
  59. 59.
    D. Dubois and H. Prade, Fuzzy Sets and Systems: Theory and Applications (Academic Press, London, 1980).MATHGoogle Scholar
  60. 60.
    D. Dubois and H. Prade, Criteria aggregation and ranking of alternatives in the framework of fuzzy set theory TIMS/Studies in the Management Sciences, 20 (1984) 209–240.MathSciNetGoogle Scholar
  61. 61.
    D. Dubois and H. Prade, Possibility Theory (Plenum Press, New York, 1988).MATHGoogle Scholar
  62. 62.
    D. Dubois, H. Prade and R.R Yager eds., Readings in Fuzzy Sets for Intelligent Systems (Morgan & Kaufmann, San Mateo, CA, 1993).Google Scholar
  63. 63.
    G. W. Evans ed., Applications of Fuzzy Set Methodologies in Industrial Engineering (Elsevier, Amsterdam, 1989).Google Scholar
  64. 64.
    M. Fedrizzi, J. Kacprzyk and S. Zadrozny, An interactive multi-user decision support system for consensus reaching processes using fuzzy logic with linguistic quantifiers, Decision Support Systems, 4 (1988) 313–327.Google Scholar
  65. 65.
    M. Fedrizzi and L. Mich, Decision using production rules, in: Proc. of Annual Conference of the Operational Research Society of Italy, September 18–10, Riva del Garda. Italy, 1991 118–121.Google Scholar
  66. 66.
    M. Fedrizzi and R. Fullér, On stability in group decision support systems under fuzzy production rules, in: R.Trappl ed., Proceedings of the Eleventh European Meeting on Cybernetics and Systems Research (World Scientific Publisher, London, 1992) 471–478.Google Scholar
  67. 67.
    M. Fedrizzi and R.Fullér, Stability in possibilistic linear programming problems with continuous fuzzy number parameters, Fuzzy Sets and Systems, 47 (1992) 187–191.MathSciNetMATHGoogle Scholar
  68. 68.
    M. Fedrizzi, M, Fedrizzi and W. Ostasiewicz, Towards fuzzy modeling in economics, Fuzzy Sets and Systems (54)(1993) 259–268.MathSciNetGoogle Scholar
  69. 69.
    J.C. Fodor and M. Roubens, Fuzzy Preference Modelling and Multicriteria Decision Aid (Kluwer Academic Publisher, Dordrecht, 1994).Google Scholar
  70. 70.
    M.J. Frank, On the simultaneous associativity of F(x, y) and x + y–F(x, y), Aequat. Math., 19 (1979) 194–226.MATHGoogle Scholar
  71. 71.
    R. Fullér and T. Keresztfalvi, On Generalization of Nguyen’s theorem, Fuzzy Sets and Systems, 41 (1991) 371–374.MathSciNetMATHGoogle Scholar
  72. 72.
    R. Fullér, On Hamacher-sum of triangular fuzzy numbers, Fuzzy Sets and Systems, 42 (1991) 205–212.MathSciNetMATHGoogle Scholar
  73. 73.
    R. Fullér, Well-posed fuzzy extensions of ill-posed linear equality systems, Fuzzy Systems and Mathematics, 5 (1991) 43–48.MATHGoogle Scholar
  74. 74.
    R. Fullér and B. Werners, The compositional rule of inference: introduction, theoretical considerations, and exact calculation formulas, Working Paper, RWTH Aachen, institut für Wirtschaftswissenschaften, No.1991/7.Google Scholar
  75. 75.
    R. Fullér, On law of large numbers for L-R fuzzy numbers, in: R. Lowen and M. Roubens eds., Proceedings of the Fourth IFSA Congress, Volume: Mathematics, Brussels, 1991 74–77.Google Scholar
  76. 76.
    R. Fullér and H.-J. Zimmermann, On Zadeh’s compositional rule of inference, in: R. Lowen and M. Roubens eds., Proceedings of the Fourth IFSA Congress, Volume: Artifical intelligence, Brussels, 1991 41–44.Google Scholar
  77. 77.
    R. Fullér and H.-J. Zimmermann, On computation of the compositional rule of inference under triangular norms, Fuzzy Sets and Systems, 51 (1992) 267–275.MathSciNetMATHGoogle Scholar
  78. 78.
    R. Fullér and T. Keresztfalvi, t-Norm-based addition of fuzzy intervals, Fuzzy Sets and Systems, 51 (1992) 155–159.MathSciNetGoogle Scholar
  79. 79.
    R. Fullér and B. Werners, The compositional rule of inference with several relations, Tatra Mountains Mathematical Publications, 1 (1992) 39–44.MathSciNetMATHGoogle Scholar
  80. 80.
    R. Fullér and H.-J. Zimmermann, Fuzzy reasoning for solving fuzzy mathematical programming problems, Working Paper, RWTH Aachen, institut für Wirtschaftswissenschaften, No.1992/01.Google Scholar
  81. 81.
    R. Fullér, A law of large numbers for fuzzy numbers, Fuzzy Sets and Systems, 45 (1992) 299–303.MathSciNetMATHGoogle Scholar
  82. 82.
    R. Fullér and H -J Zimmermann, On Zadeh’s compositional rule of inference, In: R. Lowen and M. Roubens eds., Fuzzy Logic: State of the Art, Theory and Decision Library, Series D (Kluwer Academic Publisher, Dordrecht, 1993) 193–200.Google Scholar
  83. 83.
    R. Fullér and H.-J. Zimmermann, Fuzzy reasoning for solving fuzzy mathematical programming problems, Fuzzy Sets and Systems 60 (1993) 121–133.MathSciNetMATHGoogle Scholar
  84. 84.
    R. Fullér and E. Triesch, A note on law of large numbers for fuzzy variables, Fuzzy Sets and Systems? 55(1993).Google Scholar
  85. 85.
    R. Fullér and M. Fedrizzi, On stability in multiobjective possibilistic linear programs, European Journal of Operational Reseach, 74 (1994) 179–187.MATHGoogle Scholar
  86. 86.
    R. Fullér, L. Gaio, L. Mich and A. Zorat, OCA functions for consensus reaching in group decisions in fuzzy environment, in: Proceedings of the 3rd International Conference on Fuzzy Logic, Neural Nets and Soft Computing, Iizuka, Japan, August 1–7, 1994, Iizuka, Japan, 1994, Fuzzy Logic Systems institute, 1994 101–102.Google Scholar
  87. 87.
    R. Fullér and S.Giove, A neuro-fuzzy approach to FMOLP problems, in: Proceedings of CIFT’9.4, June 1–3, 1994, Trento, Italy, University of Trento, 1994 97–101.Google Scholar
  88. 88.
    R. Fullér, Neural Fuzzy Systems? Abo Akademis tryckeri, Abo, ESF Series, A:443, 1995, 249 pages.Google Scholar
  89. 89.
    R. Fullér, Hyperknowledge representation: challenges and promises, in: P. Walden, M. Brännback, B. Back and H. Vanharanta eds., The Art and Science of Decision-Making, Abo Akademi University Press, Abo, 1996 61–89.Google Scholar
  90. 90.
    R. Fullér, OWA operators for decision making, in: C. Carlsson ed., Exploring the Limits of Support Systems, TUCS General Publications, No. 3, Turku Centre for Computer Science, Abo, 1996 85–104.Google Scholar
  91. 91.
    R. Fullér, Fuzzy Reasoning and Fuzzy Optimization? TUGS General Publications, No. 9, Turku Centre for Computer Science, Abo, 1998, 270 pages.Google Scholar
  92. 92.
    R. Goetschel and W. Voxman, Elementary fuzzy calculus, Fuzzy Sets and Systems, 18 (1986) 31–43.MathSciNetMATHGoogle Scholar
  93. 93.
    M.M. Gupta and D.H. Rao, On the principles of fuzzy neural networks, Fuzzy Sets and Systems, 61 (1994) 1–18.MathSciNetGoogle Scholar
  94. 94.
    H. Hamacher, H. Leberling and H.-J. Zimmermann, Sensitivity analysis in fuzzy linear programming, Fuzzy Sets and Systems, 1 (1978) 269–281.MathSciNetMATHGoogle Scholar
  95. 95.
    H. Hamacher, Uber logische Aggregationen nicht binär explizierter Entscheidung-kriterien (Rita G.Fischer Verlag, Frankfurt, 1978).Google Scholar
  96. 96.
    H. Hellendoorn, Closure properties of the compositional rule of inference, Fuzzy Sets and Systems, 35 (1990) 163–183.MathSciNetMATHGoogle Scholar
  97. 97.
    F. Herrera, M. Kovacs, and J. L. Verdegay, An optimum concept for fuzzified linear programming problems: a parametric approach, Tatra Mountains Mathematical Publications, 1 (1992) 57–64.MathSciNetMATHGoogle Scholar
  98. 98.
    F. Herrera, M. Kovacs, and J. L. Verdegay, Fuzzy linear programming problems with homogeneous linear fuzzy functions, in: Proc. of IPMU’92, Universitat de les Illes Balears, 1992 361–364.Google Scholar
  99. 99.
    F. Herrera, M. Kovacs, and J. L. Verdegay. Optimality for fuzzified mathematical programming problems: a parametric approach, Fuzzy Sets and Systems, 54 (1993) 279–285.MathSciNetMATHGoogle Scholar
  100. 100.
    F. Herrera, J. L. Verdegay, and M. Kovacs, A parametric approach for (g,p)fuzzified linear programming problems, Journal of Fuzzy Mathematics, 1 (1993) 699–713.MathSciNetMATHGoogle Scholar
  101. 101.
    F. Herrera, M. Kovacs, and J. L. Verdegay, Homogeneous linear fuzzy functions and ranking methods in fuzzy linear programming problems, Int. J. on Uncertainty, Fuzziness and Knowledge-based Systems, 1 (1994) 25–35.MathSciNetGoogle Scholar
  102. 102.
    F. Herrera, E. Herrera-Viedma and J. L. Verdegay, Aggregating Linguistic Preferences: Properties of the LOWA Operator, in: Proceedings of the 6th IFSA World Congress, Sao Paulo (Brasil), Vol. II, 1995 153–157.Google Scholar
  103. 103.
    F. Herrera, E. Herrera-Viedma, J.L. Verdegay, Direct approach processes in group decision making using linguistic OWA operators, Fuzzy Sets and Systems, 79 (1996) 175–190.MathSciNetMATHGoogle Scholar
  104. 104.
    F. Herrera and J.L. Verdegay, Fuzzy boolean Fuzzy Sets and Systems, 81 (1996) 57–76.MathSciNetMATHGoogle Scholar
  105. 105.
    F. Herrera, E. Herrera-Viedma, J.L. Verdegay, A model of consensus in group decision making under linguistic assessments, Fuzzy Sets and Systems, 78 (1996) 73–87.MathSciNetGoogle Scholar
  106. 106.
    F. Herrera and E. Herrera-Viedma, Aggregation Operators for Linguistic Weighted Information, IEEE Transactions on Systems, Man and Cybernetics - Part A: Systems and Humans? (27)1997 646–656.Google Scholar
  107. 107.
    F. Herrera, E. Herrera-Viedma, J L Verdegay, Linguistic Measures Basedon Fuzzy Coincidence for Reaching Consensus in Group Decision Making, International Journal of Approximate Reasoning, 16 (1997) 309–334.MATHGoogle Scholar
  108. 108.
    E. Herrera and E. Herrera-Viedma, On the linguistic OWA operator and extensions, in: R.R.Yager and J.Kacprzyk eds., The ordered weighted averaging operators: Theory, Methodology, and Applications, Kluwer Academic Publishers, Boston, 1997 60–72.Google Scholar
  109. 109.
    F. Herrera, E. Herrera-Viedma and J.L. Verdegay, Applications of the Linguistic OWA Operator in Group Decision Making, in: R.R. Yager and J. Kacprzyk eds., The ordered weighted averaging operators: Theory, Methodology, and Applications, Kluwer Academic Publishers, Boston, 1997 207–218.Google Scholar
  110. 110.
    F. Herrera, E. Herrera-Viedma, J.L. Verdegay, A rational consensus model in group decision making using linguistic assessments, Fuzzy Sets and Systems, 88 (1997) 31–49.Google Scholar
  111. 111.
    F. Herrera, E. Herrera-Viedma and J.L. Verdegay, Choice processes for non-homogeneous group decision making in linguistic setting, International Journal for Fuzzy Sets and Systems, 94 (1998) 287–308.MathSciNetGoogle Scholar
  112. 112.
    D.H. Hong and S.Y. Hwang, On the convergence of T-sum of L-R fuzzy numbers, Fuzzy Sets and Systems, 63 (1994) 175–180.MathSciNetMATHGoogle Scholar
  113. 113.
    D.H. Hong, A note on product-sum of L-R fuzzy numbers, Fuzzy Sets and Systems, 66 (1994) 381–382.MathSciNetMATHGoogle Scholar
  114. 114.
    D.H. Hong and S.Y. Hwang, On the compositional rule of inference under triangular norms, Fuzzy Sets and Systems, 66 (1994) 25–38.MathSciNetMATHGoogle Scholar
  115. 115.
    D.H. Hong A note on the law of large numbers for fuzzy numbers, Fuzzy Sets and Systems, 64 (1994) 59–61.MathSciNetGoogle Scholar
  116. 116.
    D.H. Hong A note on the law of large numbers for fuzzy numbers, Fuzzy Sets and Systems, 68 (1994) 243.MathSciNetGoogle Scholar
  117. 117.
    D.H. Hong, A note on t-norm-based addition of fuzzy intervals, Fuzzy Sets and Systems, 75 (1995) 73–76.MathSciNetMATHGoogle Scholar
  118. 118.
    D.H. Hong and Y.M. Kim, A law of large numbers for fuzzy numbers in a Banach space, Fuzzy Sets and Systems, 77 (1996) 349–354.MathSciNetMATHGoogle Scholar
  119. 119.
    D.H. Hong and C. Hwang, Upper bound of T-sum of LR-fuzzy numbers, in: Proceedings of IPMU’96 Conference (July 1–5, 1996, Granada, Spain), 1996 343–346.Google Scholar
  120. 120.
    D.H. Hong, A convergence theorem for arrays of L-R fuzzy numbers, Information Sciences, 88 (1996) 169–175.MathSciNetMATHGoogle Scholar
  121. 121.
    D.H. Hong and S.Y. Hwang, The convergence of T-product of fuzzy numbers, Fuzzy Sets and Systems, 85 (1997) 373–378.MathSciNetMATHGoogle Scholar
  122. 122.
    D.H. Hong and C. Hwang, A T-sum bound of LR-fuzzy numbers, Fuzzy Sets and Systems, 91 (1997) 239–252.MathSciNetMATHGoogle Scholar
  123. 123.
    S. Horikowa, T. Furuhashi and Y. Uchikawa, On identification of structures in premises of a fuzzy model using a fuzzy neural network, in: Proc. IEEE International Conference on Fuzzy Systems, San Francisco, 1993 661–666.Google Scholar
  124. 124.
    H. Hsi-Mei and C. Chen-Tung, Aggregation of fuzzy opinions under group decision making, Fuzzy Sets and Systems, 79 (1996) 279–285.MathSciNetGoogle Scholar
  125. 125.
    C. Huey-Kuo and C, Huey-Wen,Solving multiobjective linear programming problems–a generic approach, Fuzzy Sets and Systems, 82 (1996) 35–38.MathSciNetGoogle Scholar
  126. 126.
    Suwarna Hulsurkar, M.P. Biswal and S.B. Sinha, Fuzzy programming approach to multi-objective stochastic linear programming problems, Fuzzy Sets and Systems, 88 (1997) 173–181.MathSciNetMATHGoogle Scholar
  127. 127.
    M.L. Hussein and M.A. Abo-Sinna, A fuzzy dynamic approach to the multicriterion resource allocation problem, Fuzzy Sets and Systems, 69 (1995) 115–124.MathSciNetGoogle Scholar
  128. 128.
    M.L. Hussein and M. Abdel Aaty Maaty, The stability notions for fuzzy nonlinear programming problem, Fuzzy Sets and Systems, 85 (1997) 319–323MathSciNetMATHGoogle Scholar
  129. 129.
    M. L. Hussein, Complete solutions of multiple objective transportation problems with possibilistic coefficients, Fuzzy Sets and Systems, 93 (1998) 293–299.MathSciNetMATHGoogle Scholar
  130. 130.
    C.L. Hwang and A.S.M. Masud, Multiobjective Decision Making - Methods and Applications, A State-of-the-Art Survey (Springer-Verlag, New-York, 1979).Google Scholar
  131. 131.
    C.L. Hwang and K. Yoon, Multiple Attribute Decision Making - Methods and Applications, A State-of-the-Art Survey (Springer-Verlag, New-York, 1981).MATHGoogle Scholar
  132. 132.
    C.L. Hwang and M.J. Lin, Group Decision Making Under Multiple Criteria (Springer-Verlag, New-York, 1987).MATHGoogle Scholar
  133. 133.
    S.Y. Hwang and D.H. Hong, The convergence of T-sum of fuzzy numbers on Banach spaces, Applied Mathematics Letters 10 (1997) 129–134.MathSciNetMATHGoogle Scholar
  134. 134.
    M. Inuiguchi, H. Ichihashi and H. Tanaka, Fuzzy Programming: A Survey of Recent Developments, in: Slowinski and Teghem eds., Stochastic versus Fuzzy Approaches to Multiobjective Mathematical Programming under Uncertainty, Kluwer Academic Publishers, Dordrecht 1990, pp 45–68Google Scholar
  135. 135.
    M. Inuiguchi and M. Sakawa, A possibilistic linear program is equivalent to a stochastic linear program in a special case, Fuzzy Sets and Systems, 76 (1995) 309–317.MathSciNetMATHGoogle Scholar
  136. 136.
    M. Inuiguchi and M. Sakawa, Possible and necessary efficiency in possibilistic multiobjective linear programming problems and possible efficiency test Fuzzy Sets and Systems, 78 (1996) 231–241.MathSciNetMATHGoogle Scholar
  137. 137.
    M. Inuiguchi, Fuzzy linear programming what, why and how? Tatra Mountains Math. Publ., 13 (1997) 123–167.MathSciNetMATHGoogle Scholar
  138. 138.
    J.-S. Roger Jang, ANFIS: Adaptive-network-based fuzzy inference system, IEEE Trans. Syst., Man, and Cybernetics, 23 (1993) 665–685.Google Scholar
  139. 139.
    L.C. Jang and J.S. Kwon, A note on law of large numbers for fuzzy numbers in a Banach space, Fuzzy Sets and Systems, 98 (1998) 77–81.MathSciNetMATHGoogle Scholar
  140. 140.
    S. Jenei, Continuity in approximate reasoning, Annales Univ. Sci. Budapest, Sect. Comp., 15 (1995) 233–242.MathSciNetMATHGoogle Scholar
  141. 141.
    B. Julien, An extension to possibilistic linear programming, Fuzzy Sets and Systems, 64 (1994) 195–206.MathSciNetGoogle Scholar
  142. 142.
    J. Kacprzyk and R.R. Yager, “Softer” optimization and control models via fuzzy linguistic quantifiers, Information Sciences, 34 (1984) 157–178.MathSciNetMATHGoogle Scholar
  143. 143.
    J. Kacprzyk and R.R. Yager, Management Decision Support Systems Using Fuzzy Sets and Possibility Theory, Springer Verlag, Berlin 1985.MATHGoogle Scholar
  144. 144.
    J. Kacprzyk, Group decision making with a fuzzy linguistic majority, Fuzzy Sets and Systems, 18 (1986) 105–118.MathSciNetMATHGoogle Scholar
  145. 145.
    J. Kacprzyk and S.A. Orlovski eds., Optimization Models Using Fuzzy Sets and Possibility Theory (D.Reidel, Boston,1987).MATHGoogle Scholar
  146. 146.
    J. Kacprzyk and R.R. Yager, Using fuzzy logic with linguistic quantifiers in multiobjective decision-making and optimization: A step towards more human-consistent models, in: R. Slowinski and J. Teghem eds., Stochastic versus Fuzzy Approaches to Multiobjective Mathematical Programming under Uncertainty, Kluwer Academic Publishers, Dordrecht, 1990 331–350.Google Scholar
  147. 147.
    J. Kacprzyk and M. Fedrizzi, Multiperson decision-making Using Fuzzy Sets and Possibility Theory (Kluwer Academic Publisher, Dordrecht, 1990).MATHGoogle Scholar
  148. 148.
    J. Kacprzyk and A.O. Esogbue, Fuzzy dynamic programming- Main developments and applications, Fuzzy Sets and Systems, 81 (1996) 31–45.MathSciNetMATHGoogle Scholar
  149. 149.
    J. Kacprzyk and R.R. Yager eds., The ordered weighted averaging operators: Theory, Methodology, and Applications, Kluwer Academic Publishers, Boston, 1997.Google Scholar
  150. 150.
    O. Kaleva, Fuzzy differential equations, Fuzzy Sets and Systems, 24 (1987) 301–317.MathSciNetMATHGoogle Scholar
  151. 151.
    M.A.E. Kassem, Interactive stability of multiobjective nonlinear programming problems with fuzzy parameters in the constraints, Fuzzy Sets and Systems, 73 (1995) 235–243.MathSciNetMATHGoogle Scholar
  152. 152.
    M.A. El-Hady Kassem and E.I. Ammar, Stability of multiobjective nonlinear programming problems with fuzzy parameters in the constraints, Fuzzy Sets and Systems, 74 (1995) 343–351.MathSciNetMATHGoogle Scholar
  153. 153.
    M.A. El-Hady Kassem and E.I. Ammar, A parametric study of multiobjective NLP problems with fuzzy parameters in the objective functions Fuzzy Sets and Systems, 80 (1996) 187–196.MathSciNetMATHGoogle Scholar
  154. 154.
    M.F. Kawaguchi and T. Date, A calculation method for solving fuzzy arithmetic equations with triangular norms, in: Proceedings of Second IEEE international Conference on Fuzzy Systems, 1993 470–476.Google Scholar
  155. 155.
    M.F. Kawaguchi and T. Date, Some algebraic properties of weakly non-interactive fuzzy numbers, Fuzzy Sets and Systems, 68 (1994) 281–291.MathSciNetMATHGoogle Scholar
  156. 156.
    T. Keresztfalvi and H. Rommelfanger, Fuzzy linear programming with t-norm based extended addition, Operations Research Proceedings 1991 (Springer-Verlag, Berlin, Heidelberg, 1992) 492–499.Google Scholar
  157. 157.
    T. Keresztfalvi and M. Kovacs, g,p-fuzzification of arithmetic operations, Tatra Mountains Mathematical Publications, 1 (1992) 65–71.MathSciNetMATHGoogle Scholar
  158. 158.
    P.E. Klement and R. Mesiar, Triangular norms, Tatra Mountains Mathematical Publications, 13 (1997) 169–193.MathSciNetMATHGoogle Scholar
  159. 159.
    G.J. Klir and B. Yuan, Fuzzy Sets and Fuzzy Logic: Theory and Applications, Prentice Hall, 1995.MATHGoogle Scholar
  160. 160.
    L.T. Kóczy and K. Hirota, Ordering, distance and Closeness of Fuzzy Sets, Fuzzy Sets and Systems, 59 (1993) 281–293.MathSciNetMATHGoogle Scholar
  161. 161.
    L.T. Kóczy, A fast algorithm for fuzzy inference by compact rules, in: L.A. Zadeh and J. Kacprzyk eds., Fuzzy Logic for the Management of Uncertainty (J. Wiley, New York, 1993) 297–317.Google Scholar
  162. 162.
    S. Korner, Laws of Thought, Encyclopedia of Philosophy, Vol. 4, (MacMillan, New York 1967) 414–417.Google Scholar
  163. 163.
    B. Kosko, Neural networks and fuzzy systems, Prentice-Hall, New Jersey, 1992.MATHGoogle Scholar
  164. 164.
    B. Kosko, Fuzzy systems as universal approximators, in: Proc. IEEE 1992 Int. Conference Fuzzy Systems, San Diego, 1992 1153–1162.Google Scholar
  165. 165.
    M. Kovacs, Fuzzification of ill-posed linear systems, in: D. Greenspan and P. Rózsa, Eds., Colloquia mathematica Societitas Janos Bolyai 50, Numerical Methods, North-Holland, Amsterdam, 1988, 521–532.Google Scholar
  166. 166.
    M. Kovacs, F.P. Vasiljev and R. Fullér, On stability in fuzzified linear equality systems, Proceedings of the Moscow State University, Ser. 15, 1(1989), 5–9 (in Russian), translation in Moscow Univ. Comput. Math. Cybernet., 1 (1989), 4–9.Google Scholar
  167. 167.
    M.Kovacs and R.Fullér, On fuzzy extended systems of linear equalities and inequalities, in: A.A. Tihonov and A.A. Samarskij eds., Current Problems in Applied Mathematics, Moscow State University, Moscow, [ISBN 5–211–00342–4 1989 73 – 80 (in Russian).Google Scholar
  168. 168.
    M. Kovacs and L. H. Tran, Algebraic structure of centered M-fuzzy numbers, Fuzzy Sets and Systems, 39 (1991) 91–99.MathSciNetMATHGoogle Scholar
  169. 169.
    M. Kovacs, Linear programming with centered fuzzy numbers, Annales Univ. Sci. Budapest, Sectio Comp., 12 (1991) 159–165.MATHGoogle Scholar
  170. 170.
    M. Kovacs, An optimum concept for fuzzified mathematical programming problems, in: M. Fedrizzi, J. Kacprzyk, and M. Roubens, eds., Interactive Fuzzy Optimization, Lecture Notes Econ. Math. Systems, Vol. 368, Springer, Berlin, 1991 36–44.Google Scholar
  171. 171.
    M. Kovacs, Fuzzy linear model fitting to fuzzy observations, in: M. Fedrizzi and J. Kacprzyk, eds., Fuzzy Regression Analysis, Studies in Fuzziness, Omnitech Press, Warsaw, 1991 116–123.Google Scholar
  172. 172.
    M. Kovacs, Fuzzy linear programming problems with min-and max-extended algebraic operations on centered fuzzy numbers, in: R. Lowen and M. Roubens, eds., Proceedings of the Fourth IFSA Congress, Vol. Computer, Management & Systems Science, Brussels, 1991 125–128.Google Scholar
  173. 173.
    M. Kovacs, A stable embedding of ill-posed linear systems into fuzzy systems, Fuzzy Sets and Systems, 45 (1992) 305–312.MathSciNetMATHGoogle Scholar
  174. 174.
    M. Kovacs, A concept of optimality for fuzzified linear programming based on penalty function, in: V. Novak at.al., eds., Fuzzy Approach to Reasoning and Decision Making, Kluwer, Dordecht, 1992 133–139.Google Scholar
  175. 175.
    M. Kovacs, Fuzzy linear programming problems with min-and max-extended algebraic operations on centered fuzzy numbers. in: R. Lowen and M. Roubens, eds., Fuzzy Logic: State of Arts, Kluwer, 1993 265–275.Google Scholar
  176. 176.
    M. Kovacs, Fuzzy linear programming with centered fuzzy numbers, in: M. Delgado et.al., eds., Fuzzy Optimization: Recent Advances, Omnitech Physica Verlag, Heidelberg, 1994 135–147.Google Scholar
  177. 177.
    J.R. Layne, K.M. Passino and S. Yurkovich, Fuzzy learning control for antiskid braking system, IEEE Transactions on Contr. Syst. Tech.? 1(993) 122–129.Google Scholar
  178. 178.
    C.-C. Lee, Fuzzy logic in control systems: Fuzzy logic controller–Part I, IEEE Transactions on Syst., Man, Cybern., 20 (1990) 419–435.MATHGoogle Scholar
  179. 179.
    C.-C. Lee, Fuzzy logic in control systems: Fuzzy logic controller–Part II, IEEE Transactions on Syst., Man, Cybern., 20 (1990) 404–418.MATHGoogle Scholar
  180. 180.
    C. Lejewski, Jan Lukasiewicz, Encyclopedia of Philosophy, Vol. 5, (MacMillan, New York 1967) 104–107.Google Scholar
  181. 181.
    Hong Xing Li and Vincent C. Yen, Fuzzy sets and fuzzy decision-making, (CRC Press, Boca Raton, FL, 1995).MATHGoogle Scholar
  182. 182.
    E.H. Mamdani and S. Assilian, An experiment in linguistic synthesis with a fuzzy logic controller. International Journal of Man-Machine Studies 7 (1975) 1–13.MATHGoogle Scholar
  183. 183.
    J.K. Mattila, On some logical points of fuzzy conditional decision making, Fuzzy Sets and Systems, 20 (1986) 137–145.MathSciNetMATHGoogle Scholar
  184. 184.
    Jorma K. Mattila, Text Book of Fuzzy Logic, Art House, Helsinki, [ISBN 951884–152–7], 1998.Google Scholar
  185. 185.
    G.F. Mauer, A fuzzy logic controller for an ABS braking system, IEEE Transactions on Fuzzy Systems, 3 (1995) 381–388.Google Scholar
  186. 186.
    R. Mesiar, A note to the T-sum of L-R fuzzy numbers, Fuzzy Sets and Systems, 79 (1996) 259–261.MathSciNetMATHGoogle Scholar
  187. 187.
    R. Mesiar, Shape preserving additions of fuzzy intervals, Fuzzy Sets and Systems, 86 (1997) 73–78.MathSciNetMATHGoogle Scholar
  188. 188.
    R. Mesiar, Triangular-norm-based addition of fuzzy intervals, Fuzzy Sets and Systems, 91 (1997) 231–237.MathSciNetMATHGoogle Scholar
  189. 189.
    L. Mich, M. Fedrizzi and L. Gaio, Approximate Reasoning in the Modelling of Consensus in Group Decisions, in: E.P. Klement and W. Slany eds., Fuzzy Logic in Artifiacial intelligence, Lectures Notes in Artifiacial intelligence, Vol. 695, Springer-Verlag, Berlin, 1993 91–102.Google Scholar
  190. 190.
    D. McNeil and P, Freiberger, Fuzzy Logic (Simon and Schuster, New York, 1993).Google Scholar
  191. 191.
    T. Munkata and Y. Jani, Fuzzy systems: An overview, Communications of ACM, 37 (1994) 69–76.Google Scholar
  192. 192.
    C. V. Negoita, Fuzzy Systems (Abacus Press, Turnbridge-Wells, 1981).MATHGoogle Scholar
  193. 193.
    H.T. Nguyen, A note on the extension principle for fuzzy sets, Journal of Mathematical Analysis and Applications, 64 (1978) 369–380.MathSciNetMATHGoogle Scholar
  194. S.A. Orlovsky, Calculus of Decomposable Properties. Fuzzy Sets and Decisions (Allerton Press, 1994).Google Scholar
  195. 195.
    A.R. Ralescu, A note on rule representation in expert systems, Information Sciences, 38 (1986) 193–203.MathSciNetMATHGoogle Scholar
  196. 196.
    R.A. Riberio, Fuzzy multiple attribute decision making: A review and new preference elicitation techniques, Fuzzy Sets and Systems, 78 (1996) 155–181.MathSciNetGoogle Scholar
  197. 197.
    M. Rommelfanger and R. Hanuscheck and J. Wolf, Linear Programming with Fuzzy Objectives, Fuzzy Sets and Systems, 29 (1989) 31–48.MathSciNetMATHGoogle Scholar
  198. 198.
    H. Rommelfanger, FULPAL: An interactive method for solving (multiobjective) fuzzy linear programming problems, in: R. Slowinski and J. Teghem Jr. eds., Stochastic versus Fuzzy Approaches to Multiobjective Mathematical Programming under Uncertainty, Kluwer Academic Publishers, Dordrecht, 1990 279–299.Google Scholar
  199. 199.
    H. Rommelfanger, FULP–A PC-supported procedure for solving multicriteria linear programming problems with fuzzy data, in: M. Fedrizzi, J. Kacprzyk and M. Roubens eds., Interactive Fuzzy Optimization, Springer-Verlag, Berlin, 1991 154–167.Google Scholar
  200. 200.
    H.Rommelfanger and T.Keresztfalvi, Multicriteria fuzzy optimization based on Yager’s parametrized t-norm, Foundations of Computing and Decision Sciences, 16 (1991) 99–110.MathSciNetMATHGoogle Scholar
  201. 201.
    H. Rommelfanger, Fuzzy Decision Support-Systeme, Springer-Verlag, Heidelberg, 1994 (Second Edition).MATHGoogle Scholar
  202. 202.
    H. Rommelfanger, Fuzzy linear programming and applications, European Journal of Operational Research, 92 (1996) 512–527.MATHGoogle Scholar
  203. 203.
    B. Schweizer and A. Sklar, Associative functions and abstract semigroups, Publ. Math. Debrecen, 10 (1963) 69–81.MathSciNetGoogle Scholar
  204. 204.
    R. Slowiriski, A multicriteria fuzzy linear programming method for water supply system development planning, Fuzzy Sets and Systems, 19 (1986) 217–237.MathSciNetGoogle Scholar
  205. 205.
    R. Slowinski and J. Teghem Jr. Fuzzy versus Stochastic Approaches to Multicriteria Linear Programming under Uncertainty, Naval Research Logistics, 35 (1988) 673–695.MathSciNetMATHGoogle Scholar
  206. 206.
    R. Slowiríski and J. Teghem Jr. Stochastic versus Fuzzy Approaches to Multiobjective Mathematical Programming under Uncertainty, Kluwer Academic Publishers, Dordrecht 1990.Google Scholar
  207. 207.
    T. Sudkamp, Similarity, interpolation, and fuzzy rule construction, Fuzzy Sets and Systems, 58 (1993) 73–86.MathSciNetGoogle Scholar
  208. 208.
    T.Takagi and M. Sugeno, Fuzzy identification of systems and its applications to modeling and control, IEEE Trans. Syst. Man Cybernet., 1985, 116–132.Google Scholar
  209. 209.
    M. Sugeno, Industrial Applications of Fuzzy Control (North Holland, Amsterdam, 1992).Google Scholar
  210. 210.
    T. Tilli, Fuzzy Logik: Grundlagen, Anwendungen, Hard-and Software (Franzis-Verlag, München, 1992).Google Scholar
  211. 211.
    T. Tilli, Automatisierung mit Fuzzy Logik (Franzis-Verlag, München, 1992).Google Scholar
  212. 212.
    I.B. Turksen, Fuzzy normal forms, Fuzzy Sets and Systems, 69 (1995) 319–346.MathSciNetGoogle Scholar
  213. 213.
    L.-X. Wang and J.M. Mendel, Fuzzy basis functions, universal approximation, and orthogonal least-squares learning, IEEE Transactions on Neural Networks, 3 (1992) 807–814.Google Scholar
  214. 214.
    L.-X. Wang, Fuzzy systems are universal approximators, in: Proc. IEEE 1992 Int. Conference Fuzzy Systems, San Diego, 1992 1163–1170.Google Scholar
  215. 215.
    S. Weber, A general concept of fuzzy connectives, negations, and implications based on t-norms and t-conorms, Fuzzy Sets and Systems? 11(1983) 115–134.MathSciNetMATHGoogle Scholar
  216. 216.
    B. Werners, Interaktive Entscheidungsunterstützung durch ein flexibles mathematisches Programmierungssystem, Minerva, Publikation, München, 1984.Google Scholar
  217. 217.
    B. Werners, Interactive Multiple Objective Programming Subject to Flexible Constraints, European Journal of Operational Research, 31 (1987) 324–349.MathSciNetGoogle Scholar
  218. 218.
    B. Werners and H.-J. Zimmermann, Evaluation and selection of alternatives considering multiple criteria, in: A.S. Jovanovic, K.F. Kussmaul, A.C. Lucia and P.P. Bonissone eds., Proceedings of an International Course on Expert Systems in Structural Safety Assessment (Stuttgart, October 2–4, 1989) Springer-Verlag, Heilderberg, 1989 167–183.Google Scholar
  219. 219.
    R.R. Yager, Fuzzy decision making using unequal objectives, Fuzzy Sets and Systems, 1 (1978) 87–95.MATHGoogle Scholar
  220. 220.
    R.R. Yager, A new methodology for ordinal multiple aspect decisions based on fuzzy sets, Decision Sciences 12 (1981) 589–600.MathSciNetGoogle Scholar
  221. 221.
    R.R. Yager ed., Fuzzy Sets and Applications. Selected Papers by L.A.Zadeh (John Wiley & Sons, New York, 1987).Google Scholar
  222. 222.
    R.R. Yager, Ordered weighted averaging aggregation operators in multi-criteria decision making, IEEE Trans. on Systems, Man and Cybernetics? 18(1988)183–190.MathSciNetMATHGoogle Scholar
  223. 223.
    R.R. Yager, Families of OWA operators, Fuzzy Sets and Systems, 59 (1993) 125–148.MathSciNetMATHGoogle Scholar
  224. 224.
    R.R. Yager, Fuzzy Screening Systems, in: R. Lowen and M. Roubens eds., Fuzzy Logic: State of the Art (Kluwer, Dordrecht, 1993) 251–261.Google Scholar
  225. 225.
    R.R. Yager, Aggregation operators and fuzzy systems modeling, Fuzzy Sets and Systems, 67 (1994) 129–145.MathSciNetMATHGoogle Scholar
  226. 226.
    R.R. Yager and D. Filev, Essentials of Fuzzy Modeling and Control (Wiley, New York, 1994).Google Scholar
  227. 227.
    R.R. Yager, Fuzzy sets as a tool for modeling, in: J. van Leeuwen ed., Computer Science Today: Recent Trends and Development, Springer-Verlag, Berlin, 1995 536–548.Google Scholar
  228. 228.
    R.R. Yager, Constrained OWA aggregation, Fuzzy Sets and Systems, 81 (1996) 89–101.MathSciNetGoogle Scholar
  229. 229.
    R.R. Yager, Including importances in OWA aggregations using fuzzy systems modeling, Technical Report, #MII-1625, Mashine Intelligence Institute, Iona College, New York, 1996.Google Scholar
  230. 230.
    R.R. Yager, On the inclusion of importances in OWA aggregations, in: R.R. Yager and J. Kacprzyk eds., The ordered weighted averaging operators: Theory, Methodology, and Applications, Kluwer Academic Publishers, Boston, 1997 41–59.Google Scholar
  231. 231.
    T. Yamakawa and K. Sasaki, Fuzzy memory device, in: Proceedings of 2nd IFSA Congress, Tokyo, Japan, 1987 551–555.Google Scholar
  232. 232.
    T Yamakawa, Fuzzy controller hardware system, in: Proceedings of 2nd IFSA Congress, Tokyo, Japan, 1987.Google Scholar
  233. 233.
    T. Yamakawa, Fuzzy microprocessors–rule chip and defuzzifier chip, in: International Workshop on Fuzzy System Applications, lizuka, Japan, 1988 51–52.Google Scholar
  234. 234.
    J. Yen, R. Langari and L.A. Zadeh eds., Industrial Applications of Fuzzy Logic and Intelligent Systems (IEEE Press, New York, 1995).MATHGoogle Scholar
  235. 235.
    L.A. Zadeh, Fuzzy Sets, Information and Control, 8 (1965) 338–353.MathSciNetMATHGoogle Scholar
  236. 236.
    L.A. Zadeh, Towards a theory of fuzzy systems, in: R.E. Kalman and N. DeClaris eds., Aspects of Network and System Theory (Hort, Rinehart and Winston, New York, 1971) 469–490.Google Scholar
  237. 237.
    L.A. Zadeh, Outline of a new approach to the analysis of complex systems and decision processes, IEEE Transanctins on Systems, Man and Cybernetics, 3 (1973) 28–44.MathSciNetMATHGoogle Scholar
  238. 238.
    L.A. Zadeh, Concept of a linguistic variable and its application to approximate reasoning, I, II, III, Information Sciences, 8(1975) 199–249, 301–357; 9 (1975) 43–80.Google Scholar
  239. 239.
    L.A. Zadeh, Fuzzy sets as a basis for a theory of possibility, Fuzzy Sets and Systems, 1 (1978) 3–28.MathSciNetMATHGoogle Scholar
  240. 240.
    L.A. Zadeh, A theory of approximate reasoning, In: J. Hayes, D. Michie and L.I. Mikulich eds., Machine Intelligence, Vol.9 (Halstead Press, New York, 1979) 149–194.Google Scholar
  241. 241.
    L.A. Zadeh, A computational theory of dispositions, Int. Journal of Intelligent Systems, 2 (1987) 39–63.MATHGoogle Scholar
  242. 242.
    L.A. Zadeh, Knowledge representation in fuzzy logic, In: R.R. Yager and L.A. Zadeh eds., An introduction to fuzzy logic applications in intelligent systems (Kluwer Academic Publisher, Boston, 1992) 2–25.Google Scholar
  243. 243.
    H.-J. Zimmermann, Description and optimization of fuzzy systems, International Journal of General Systems, 2 (1975) 209–215.Google Scholar
  244. 244.
    H -J Zimmermann, Description and optimization of fuzzy system, International Journal of General Systems, 2 (1976) 209–215.MATHGoogle Scholar
  245. 245.
    H.-J. Zimmermann, Fuzzy programming and linear programming with several objective functions, Fuzzy Sets and Systems, 1 (1978) 45–55.MathSciNetMATHGoogle Scholar
  246. 246.
    H.-J. Zimmermann and P. Zysno, Latent connectives in human decision making, Fuzzy Sets and Systems, 4 (1980) 37–51.MATHGoogle Scholar
  247. 247.
    H.-J. Zimmermann, Applications of fuzzy set theory to mathematical programming, Information Sciences, 36 (1985) 29–58.MathSciNetMATHGoogle Scholar
  248. 248.
    H.-J. Zimmermann, Fuzzy Set Theory and Its Applications, Dordrecht, Boston 1985.Google Scholar
  249. 249.
    H.J. Zimmermann, Fuzzy set theory and mathematical programming, in: A. Jones et al. eds., Fuzzy Sets Theory and Applications, 1986, D.Reidel Publishing Company, Dordrecht, 99–114.Google Scholar
  250. 250.
    H.-J. Zimmermann, Fuzzy Sets, decision-making and Expert Systems, Kluwer Academic Publisher, Boston 1987.Google Scholar
  251. 251.
    H.-J. Zimmermann and B.Werners, Uncertainty representation in knowledge-based systems, in: A.S. Jovanovic, K.F. Kussmal, A.C. Lucia and P.P. Bonissone eds., Proc. of an International Course on Expert Systems in Structural Safety Assessment Stuttgart, October 2–4, 1989, (Springer-Verlag, Berlin, Heidelberg, 1989) 151–166.Google Scholar
  252. 252.
    H.-J. Zimmermann, decision-making in ill-structured environments and with multiple criteria, in: Bana e Costa ed., Readings in Multiple Criteria Decision Aid Springer Verlag, 1990 119–151.Google Scholar
  253. 253.
    H -J Zimmermann, Cognitive sciences, decision technology, and fuzzy sets, Information Sciences, 57–58 (1991) 287–295.Google Scholar
  254. 254.
    H.-J. Zimmermann, Fuzzy Mathematical Programming, in: Stuart C. Shapiro ed., Encyclopedia of Artificial Intelligence, John Wiley & Sons, Inc., Vol. 1, 1992 521–528.Google Scholar
  255. 255.
    H.-J. Zimmermann, Methods and applications of fuzzy mathematical programming, in: R.R. Yager and L.A. Zadeh eds., An Introduction to Fuzzy Logic Applications in Intelligent Systems, Kluwer Academic Publisher, Boston, 1992 97–120.Google Scholar
  256. 256.
    H.-J. Zimmermann, Fuzzy Decisions: Approaches, Problems and Applications, in: Publications Series of the Japanese-German Center, Berlin, Series 3, Vol. 8, 1994 115–136.Google Scholar
  257. 257.
    H.-J. Zimmermann, Fuzzy Mathematical Programming, in: Tomas Gal and Harvey J. Greenberg eds., Advances in Sensitivity Analysis and Parametric Programming, Kluwer Academic Publishers, 1997 1–40.Google Scholar
  258. 258.
    H.-J. Zimmermann, A Fresh Perspective on Uncertainty Modeling: Uncertainty vs. Uncertainty Modeling. in: Bilal M. Ayyub and Madan M. Gupta eds., Uncertainty Analysis in Engineering and Sciences: Fuzzy Logic, Statistics, and Neural Network Approach, International Series in Intelligent Technologies, Kluwer Academic Publishers, 1997 353–364.Google Scholar
  259. 259.
    H.-J. Zimmermann, Fuzzy logic on the frontiers of decision analysis and expert systems, in: Proceedings of First International Workshop on Preferences and Decisions, Trento, June 5–7, 1997, University of Trento, 1997 97–103.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • Robert Fullér
    • 1
    • 2
  1. 1.Department of Operations ResearchEötvös Lorànd UniversityBudapestHungary
  2. 2.Institute of Advanced Management Systems ResearchÅbo Akademi UniversityTurkuFinland

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