Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Bücher
Zeitschriften
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
SLX-Digitalkonferenz: Zukunftswerkstatt 2024

Mehr Umsatz mit Top-Kontakten

Am 7. Mai erfahren Sie, wie Vertriebsteams Leadgenerierung, Leadnurturing und Leadstrategien effizient steuern können.
Erweiterte Suche
Anmelden
nach oben
Erschienen in:
Buchtitelbild

2016 | OriginalPaper | Buchkapitel

The Emergence of Fuzzy Sets: A Historical Perspective

verfasst von : Didier Dubois, Henri Prade

Erschienen in: Fuzzy Logic in Its 50th Year

Verlag: Springer International Publishing

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

This paper tries to suggest some reasons why fuzzy set theory came to life 50 years ago by pointing out the existence of streams of thought in the first half of the XXth century in logic, linguistics and philosophy, that paved the way to the idea of moving away from the Boolean framework, through the proposal of many-valued logics and the study of the vagueness phenomenon in natural languages. The founding paper in fuzzy set theory can be viewed as the crystallization of such ideas inside the engineering arena. Then we stress the point that this publication in 1965 was followed by several other seminal papers in the subsequent 15 years, regarding classification, ordering and similarity, systems science, decision-making, uncertainty management and approximate reasoning. The continued effort by Zadeh to apply fuzzy sets to the basic notions of a number of disciplines in computer and information sciences proved crucial in the diffusion of this concept from mathematical sciences to industrial applications.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Jetzt informieren
Nächstes Kapitel Fuzzy Decision Making: Its Pioneers and Supportive Environment
Literatur
1.
Baudrit, C., Guyonnet, D., Dubois, D.: Joint propagation and exploitation of probabilistic and possibilistic information in risk assessment. IEEE Trans. Fuzzy Syst. 14, 593–608 (2006)
2.
Beliakov, G., Pradera, A., Calvo, T.: Aggregation Functions: A Guide for Practitioners. Studies in Fuzziness and Soft Computing, vol. 221. Springer (2007)
3.
4.
5.
Bezdek, J., Keller, J., Krishnapuram, R., Pal, N.: Fuzzy Models for Pattern Recognition and Image processing. Kluwer (1999)
6.
Bodenhofer, U., De Baets, B., Fodor, J.C.: A compendium of fuzzy weak orders: Representations and constructions. Fuzzy Sets Syst. 158(8), 811–829 (2007)MathSciNetCrossRefMATH
7.
Black, M., Vagueness, M.: Phil. Sci. 4, 427–455 (1937) (Reprinted in Language and Philosophy: Studies in Method. Cornell University Press, pp. 23–58. Ithaca, London, 1949. Also in Int. J. Gen. Syst. 17, 107–128, 1990)
8.
Bosc, P., Pivert, O.: Modeling and querying uncertain relational databases: a survey of approaches based on the possible world semantics. Int. J. Uncertainty, Fuzziness Knowl. Based Syst. 18(5), 565–603 (2010)
9.
10.
Couso, I., Dubois, D., Sanchez, L.: Random Sets and Random Fuzzy Sets as Ill-Perceived Random Variables. Springer, Springer Briefs in Computational Intelligence, 2014
11.
De Baets, B., Dubois, D., Hüllermeier, E.: Special issue celebrating the 50th anniversary of fuzzy sets. Fuzzy Sets Syst 281, 1–308 (2015)
12.
De Finetti, B.: La logique de la probabilité, Actes Congrés Int. de Philos. Scient., Paris (1935) (Hermann et Cie Editions. Paris, pp. IV1–IV9, 1936)
13.
Dubois, D.: Have fuzzy sets anything to do with vagueness? (with discussion) In: Cintula, P., Fermüller, C. (eds.) Understanding Vagueness-Logical, Philosophical and Linguistic Perspectives, vol. 36 of Studies in Logic. College Publications, pp. 317–346 (2012)
14.
Dubois, D., Esteva, F., Godo, L., Prade, H.: Fuzzy-set based logics—an history-oriented presentation of their main developments. In: Gabbay, D.M., Woods, J. (Eds.) Handbook of The History of Logic. The Many Valued and Nonmonotonic Turn in Logic, vol. 8, Elsevier, pp. 325–449 (2007)
15.
Dubois, D., Fargier, H., Fortemps, P.: Fuzzy scheduling: modelling flexible constraints vs. coping with incomplete knowledge. Eur. J. Oper. Res. 147(2), 231–252 (2003)MathSciNetCrossRefMATH
16.
Dubois, D., Fargier, H., Prade, H.: Possibility theory in constraint satisfaction problems: handling priority, preference and uncertainty. Appl. Intell. 6, 287–309 (1996)CrossRefMATH
17.
Dubois, D., Ostasiewicz, W., Prade, H.: Fuzzy sets: history and basic notions. In: Dubois, D. Prade, H. (eds.) Fundamentals of Fuzzy Sets. The Handbooks of Fuzzy Sets Series, Kluwer, pp. 21–124 (2000)
18.
Dubois, D., Prade, H.: Possibility Theory: An Approach to Computerized Processing of Uncertainty. Plenum Press, New York (1988)
19.
Dubois, D., Prade, H.: The three semantics of fuzzy sets. Fuzzy Sets Syst. 90, 141–150
20.
Dubois, D., Prade, H.: Gradual elements in a fuzzy set. Soft. Comput. 12, 165–175 (2008)CrossRefMATH
21.
Dubois, D., Prade, H.: Gradualness, uncertainty and bipolarity: making sense of fuzzy sets. Fuzzy Sets Syst. 192, 3–24 (2012)MathSciNetCrossRefMATH
22.
Dubois, D., Prade, H.: Possibilistic logic—an overview. In: Siekmann, J., Gabbay, D.M., Woods, J. (eds.) Handbook of the History of Logic. Computational Logic, vol. 9, pp. 283–342 (2014)
23.
Dubois, D., Prade, H.: Possibility theory and its applications: where do we stand? In: Kacprzyk, J., Pedrycz, W. (eds.) Handbook of Computational Intelligence, pp. 31–60. Springer (2015)
24.
25.
Fodor, J., Roubens, M.: Fuzzy Preference Modelling and Multicriteria Decision Support. Kluwer Academic Publication (1994)
26.
Gil, M.A., González-Rodriguez, G., Kruse, R. (eds.) Statistics with imperfect data. Spec. Issue Inf. Sci. 245, 1–3 (2013)
27.
28.
Gottwald, S.: Fuzzy sets theory: some aspects of the early development, In: Skala, H.J., Termini, S., Trillas, E., (eds.) Aspects of Vagueness, pp. 13–29. D. Reidel (1984)
29.
Hájek, P.: Metamathematics of Fuzzy Logic, Trends in Logic, vol. 4. Kluwer, Dordercht (1998)CrossRefMATH
30.
Hoehle, U., Rodabaugh, S.E. (eds.) Mathematics of Fuzzy Sets: Logic, Topology, and Measure Theory, The Handbooks of Fuzzy Sets Series, vol. 3. Kluwer Academic Publishers, Dordrecht (1999)
31.
Inuiguchi, M., Ramik, J.: Possibilistic linear programming: a brief review of fuzzy mathematical programming and a comparison with stochastic programming in portfolio selection problem. Fuzzy Sets Syst. 111(1), 3–28 (2000)
32.
Inuiguchi, M., Watada, J., Dubois, D. (eds.) Special issue on fuzzy modeling for optimisation and decision support. Fuzzy Sets Syst. 274 (2015)
33.
Kaplan, A.: Definition and specification of meanings. J. Phil. 43, 281–288 (1946)CrossRef
34.
Kaplan, A., Schott, H.F.: A calculus for empirical classes. Methods III, 165–188 (1951)
35.
Kleene, S.C.: Introduction to Metamathematics. North Holland Pub. Co., Amsterdam (1952)MATH
36.
Lodwick, W.A., Dubois, D.: Interval linear systems as a necessary step in fuzzy linear systems. Fuzzy Sets Syst. 281, 227–251 (2015)MathSciNetCrossRef
37.
Lodwick, W.A., Oberguggenberger, M. (eds.) Differential equations over fuzzy spaces—theory, applications, and algorithms. Spec Issue Fuzzy Sets Syst. 230, 1–162 (2013)
38.
Łukasiewicz, J.: Philosophical remarks on many-valued systems of propositional logic (1930) (Reprinted in Selected works. In Borkowski (ed.) Studies in Logic and the Foundations of Mathematics, pp. 153–179. North-Holland, Amsterdam, 1970)
39.
Mauris, G.: Possibility distributions: a unified representation of usual direct-probability-based parameter estimation methods. Int. J. Approx. Reasoning 52(9), 1232–1242 (2011)MathSciNetCrossRefMATH
40.
Menger, K.: Ensembles flous et fonctions aleatoires. Comptes Rendus de lAcadmie des Sciences de Paris 232, 2001–2003 (1951)MathSciNetMATH
41.
Meseguer, P., Rossi, F., Schiex, T.: Soft Constraints, Chapter 9 in Foundations of Artificial Intelligence, vol. 2, Elsevier, pp. 281–328 (2006)
42.
43.
Muzzioli, S., Ruggieri, A., De Baets, B.: A comparison of fuzzy regression methods for the estimation of the implied volatility smile function. Fuzzy Sets Syst. 266, 131–143 (2015)MathSciNetCrossRef
44.
Novák, V.: Are fuzzy sets a reasonable tool for modeling vague phenomena? Fuzzy Sets Syst. 156(3), 341–348 (2005)
45.
Ostasiewicz, W.: Pioneers of fuzziness. Busefal 46, 4–15 (1991)
46.
Ostasiewicz, W.: Half a century of fuzzy sets. Supplement to Kybernetika 28:17–20, 1992 (Proc. of the Inter. Symp. on Fuzzy Approach to Reasoning and Decision Making, Bechyne, Czechoslovakia, June 25-29, 1990)
47.
Peirce, C.S.: Collected papers of Charles sanders Peirce. In: Hartshorne, C., Weiss, P. (eds.) Harvard University Press. Cambridge, MA (1931)
48.
49.
Russell, B., Vagueness, B.: Austr. J. Philos. 1, 84–92 (1923)
50.
Seising, R.: Not, or, and,—not an end and not no end! The “Enric-Trillas-path” in fuzzy logic. In: Seising, R., Argüelles Méndez, L. (eds.) Accuracy and fuzziness. A Life in Science and Politics. A festschrift book to Enric Trillas Ruiz, pp. 1–59, Springer (2015)
51.
Shackle, G.L.S.: Expectation in Economics, 2nd edn. Cambridge University Press, UK (1949)
52.
Shackle, G.L.S.: Decision, Order and Time in Human Affairs, 2nd edn. Cambridge University Press, UK (1961)
53.
Smith, P., Keefe, R.: Vagueness: A Reader. MIT Press, Cambridge, MA (1997)
54.
55.
56.
Williamson, T.: Vagueness. Routledge, London (1994)
57.
Wittgenstein, L.: Philosophical Investigations. Macmillan, New York (1953)MATH
58.
Zadeh, L.A.: Thinking machines. A new field in electrical engineering. Columbia Eng. Q. 3, 12–13, 30–31 (1950)
59.
Zadeh, L.A.: From circuit theory to system theory. Proc. IRE 50, 856–865 (1962)
60.
61.
Zadeh, L.A.: Fuzzy sets and systems. In: Fox, J. (Ed.) Systems Theory, pp .29-37. Polytechnic Press, Brooklyn, NY (1966) (Proceedings of Symposium on System Theory. New York, 20–22 Apr 1965, (reprinted in Int. J. General Syst., 17, 129–138, 1990)
62.
63.
64.
Zadeh, L.A.: Biological applications of the theory of fuzzy sets and systems. In: Kilmer, W.L., Proctor, L.D., Brown, L., et al. (eds.) Biocybernetics of the Central Nervous System (with a discussion by Boston, pp. 199–206 (discussion pp. 207–212) (1969)
65.
66.
67.
Zadeh, L.A.: Toward a theory of fuzzy systems. In: Kalman, R.E., De Claris, N. (eds.) Aspects of Network and System Theory, pp. 469–490. Holt, Rinehart and Winston, New York, (1971) (originally NASA Contractor Report 1432, Sept. 1969)
68.
Zadeh, L.A.: A rationale for fuzzy control. J. of Dyn. Syst. Measur. Control Trans. ASME, 3–4 (1972) (March issue)
69.
Zadeh, L.A.: Outline of a new approach to the analysis of complex systems and decision processes. IEEE Trans. Syst. Man Cybern. 3(1), 28–44 (1973)
70.
71.
Zadeh, L.A.: Calculus of fuzzy restrictions. In: Zadeh, L.A., Fu, K.S., Tanaka, K., Shimura, M. (eds.) Fuzzy sets and Their Applications to Cognitive and Decision Processes. Proceedings of U.S.-Japan Seminar on Fuzzy Sets and Their Applications. Berkeley, 1–4 July, 1974 (Academic Press, pp. 1–39, 1975)
72.
Zadeh, L.A.: The concept of a linguistic variable and its application to approximate reasoning. Inf. Sci., Part I, 8(3), 199–249; Part II, 8(4), 301–357; Part III, 9(1), 43–80 (1975)
73.
74.
75.
Zadeh, L.A.: A theory of approximate reasoning. In: Hayes, J.E., Mitchie, D., Mikulich, L.I. (eds.) Machine Intelligence, vol. 9, pp. 149–194 (1979)
76.
Zadeh, L.A.: Fuzzy sets and information granularity. In: Gupta, M.M., Ragade, R.K., Yager, R.R. (eds.) Advances in Fuzzy Set Theory and Applications, pp. 3–18. North-Holland (1979)
77.
Zadeh, L.A.: Possibility theory and soft data analysis. In: Cobb, L., Thrall, R. (eds.) Mathematical Frontiers of Social and Policy Sciences, pp. 69–129. Westview Press, Boulder Co (1982)
78.
Zadeh, L.A.: Precisiation of meaning via translation into PRUF. In: Vaina, L., Hintikka, J. (eds.) Cognitive Constraints on Communication, pp. 373–402. Reidel, Dordrecht (1984)
79.
Zadeh, L.A.: Syllogistic reasoning in fuzzy logic and its application to usuality and reasoning with dispositions. IEEE Trans. Syst. Man Cybern. 15(6), 754–763 (1985)MathSciNetCrossRefMATH
80.
Zadeh, L.A.: Knowledge representation in fuzzy logic. IEEE Trans. Knowl. Data Eng. 1(1), 89–100 (1989)CrossRef
81.
Zadeh, L.A.: The calculus of fuzzy if-then rules. AI Expert 7(3), 23–27 (1992)MathSciNet
82.
83.
Zadeh, L.A.: Toward a theory of fuzzy information granulation and its centrality in human reasoning and fuzzy logic. Fuzzy Sets Syst. 90, 111–128 (1997)MathSciNetCrossRefMATH
84.
Zadeh, L.A.: Generalized theory of uncertainty (GTU)—principal concepts and ideas. Comput. Stat. Data Anal. 51, 15–46 (2006)MathSciNetCrossRefMATH
85.
86.
Zimmermann, H.-J.: Fuzzy programming and linear programming with several objective functions. Fuzzy Sets Syst. 1, 45–55 (1978)MathSciNetCrossRefMATH
Metadaten
Titel
The Emergence of Fuzzy Sets: A Historical Perspective
verfasst von
Didier Dubois
Henri Prade
Copyright-Jahr
2016
Buch
Fuzzy Logic in Its 50th Year

Print ISBN: 978-3-319-31091-6

Electronic ISBN: 978-3-319-31093-0

Copyright-Jahr: 2016

DOI
https://doi.org/10.1007/978-3-319-31093-0_1