Zusammenfassung
Dieser Artikel bietet einen Überblick über die Entwicklung und Zusammenhänge der einzelnen Elemente der Fuzzy-Logik, wovon Fuzzy-Set-Theorie die Grundlage bildet. Die Grundproblematik besteht in der Handhabung von linguistischen Informationen, die häufig durch Ungenauigkeit gekennzeichnet sind. Die verschiedenen technischen Anwendungen von Fuzzy-Logik bieten eine Möglichkeit, intelligentere Computersysteme zu konstruieren, die mit unpräzisen Informationen umgehen können. Solche Systeme sind Indizien für die Entstehung einer neuen Ära des Cognitive-Computing, die in diesem Artikel ebenfalls zur Sprache kommt. Für das bessere Verständnis wird der Artikel mit einem Beispiel aus der Meteorologie (d. h. Schnee in Adelboden) begleitet.
References
Badredine A (2005) Fuzzy decision making in politics: a linguistic fuzzy set approach (LFSA). Pol Anal 13(1):23–56
Bar-Cohen Y (2006) Biomimetics – using nature to inspire human innovation. Bioinspiration Biomimetics 1(1):1–12
Berners-Lee T, Hendler J, Lassila O (2001) The Semantic Web. Sci Am 29–37
Dernoncourt F (2011) Introduction to fuzzy logic. MIT
Dubois D, Prade H (1998) An introduction to fuzzy systems. Clin Chim Acta 270(1):3–29
Froese N. Aristoteles: Logik und Methodik in der Antike. Logische Grundprinzipien, der Syllogismus und antike Wissenschaftsphilosophie. http://www.antike-griechische.de/Aristoteles.pdf, letzter Zugriff: 15.09.2015
Haun M (2014) Cognitive Computing. Steigerung des systemischen Intelligenzprofils. Springer, Berlin Heidelberg
Herrera F, Martinez L (2000) A 2-tuple fuzzy linguistic representation, model for computing with words. IEEE T Fuzzy Syst 8(6):746–752
Hobbs JR (1985) Granularity. In: Proceedings of International Joint Conference on Artificial Intelligence (IJCAI), Los Angeles, CA, pp 432–435
Jafar OAM, Sivakumar R (2013) A Comparative Study of Hard and Fuzzy Data Clustering Algorithms with Cluster Validity Indices. In: Proceedings of International Conference on ,,Emerging Research in Computing, Information, Communication and Applications (ERCICA 2013)“, Elsevier Publications, pp 775–782
Kaufmann M, Portmann E, Fathi M (2012) A concept of semantics extraction from web data by induction of fuzzy ontologies. In: International Workshop on Uncertainty Reasoning for the Semantic Web
Kaufmann M, Portmann E (2015) Biomimetics in design-oriented information systems research. In: Donnellan B, Gleasure R, Helfert M, Kenneally J, Rothenberger M, Chiarini Tremblay M, Vandermeert D, Winter R (eds) At the Vanguard of Design Science: First Impressions and Early Finding from Ongoing Research Research-in-Progress Papers and Poster Presentations from the 10th International Conference, DESRIST, Dublin, Ireland, pp 53–60
Klir GJ, Yuan B (1995) Fuzzy Sets and Fuzzy Logic – Theory and Applications. Prentice-Hall, New York
Kosko B (1986) Fuzzy cognitive maps. Int J Man Mach Stud 24(1):65–75
Lawry J (2001) A methodology for computing with words. Int J Approx Reason 28(2):51–89
Loucks DP, van Beek E, Stedinger JR, Dijkman JPM, Viallers MT (2005) Water Resources Systems Planning and Management: An Introduction to Methods, Models and Application. UNESCO, Paris, pp 135–144
Mendel JM (2007) Computing with words and its relationships with fuzzistics. Inform Sciences 177(4):988–1006
Mendel JM, Zadeh LA, Trillas E, Yager R, Lawry J, Hagas H, Guadarrama S (2010) What computing with words means to me. IEEE Comput Intell Mag 20–26
Papageorgiou EI, Salmeron JL (2013) A review of fuzzy cognitive maps research during the last decade. IEEE T Fuzzy Syst 21(1):66–79
Pedrycz W (2010) The design of cognitive maps: a study in synergy of granular computing and evolutionary optimization. Expert Syst Appl 37(10):7288–7294
Pedrycz W, Jastrzebska A, Homenda W (2015) Design of fuzzy cognitive maps for modeling time series. IEEE T Fuzzy Syst
Portmann E, Kaufmann MA, Graf C (2012) A distributed, semiotic-inductive, and human-oriented approach to web-scale knowledge retrieval. In: Proceedings of the 2012 International Workshop on Web-scale Knowledge Representation, Retrieval and Reasoning, ACM, New York, pp 1–8
Rappaport WJ (2003) What did you mean by that? Misunderstanding, negotiation, and syntactic semantics. Mind Mach 13:397–427
Reformat M, Ly C (2009) Ontological approach to development of computing with words based systems. Int J Approx Reason 50(1):72–91
Siemens G (2005) Connectivism: a learning theory for the digital age. Int J Instr Tech Dist Learn 2(1):3–10
Spinas O. Zur Geschichte der Logik. https://www.math.uni-kiel.de/logik/de/arbeitsgruppe-logik/zur-geschichte-der-logik, letzter Zugriff: 1.6.2015
Strahm T (1999) Logik in Informatik, Mathematik und Philosophie. Vortrag anlässlich der Veranstaltung Theodor-Kocher-Preis der Universität Bern 1998
Tolman EC (1948) Cognitive maps in rats and men. Psychol Rev 55(4):189–208
Wang Y (2006) Keynote speech: cognitive informatics – towards future generation computers that think and feel. In: Proceedings of the 5th IEEE International Conference on Cognitive Informatics (ICCI’06), Beijing, China, IEEE CS Press, pp 3–7
Yager RR, Filev D (1998) Operations for granular computing: mixing words and numbers. In: Proceedings of the FUZZ-IEEE World Congress on Computational Intelligence, Anchorage, pp 123–128
Yao YY (2000) Granular computing: basic issues and possible solutions. In: Proceedings of the 5th Conference on Information Sciences, Atlantic, NJ, USA, vol 1, pp 186–189
Yao YY (2006) Three perspectives of granular computing. In: Proceedings of the International Forum on Theory of GrC from Rough Set Perspective. J Nanchang Inst Technol 25(2):16–21
Ying M (2002) A formal model of computing with words. IEEE T Fuzzy Syst 10(5):640–652
Zadeh LA (1965) Fuzzy sets. Inform Control 8:338–353
Zadeh LA(1975) The concept of a linguistic variable and its applications to approximate reasoning – I. Inform Sci 8:199–249
Zadeh LA (1988) Fuzzy logic. IEEE Computer 21(4):83–93
Zadeh LA (1996) Fuzzy logic = computing with words. IEEE T Fuzzy Syst 4(2):103–111
Zadeh LA (1997) Toward a theory of fuzzy information granulation and its centrality in human reasoning and fuzzy logic. Fuzzy Set Syst 90:111–127
Zadeh LA (1998) Some reflections on soft computing, granular computing and their roles in the conception, design and utilization of information/intelligent systems. Soft Comput 2:23–25
Zadeh LA (2001) From computing with numbers to computing with words – from manipulation of measurements to manipulation of perceptions. Ann NY Acad Sci 929(1):221–252
Zadeh LA (2005) Toward a generalized constraint of uncertainty (GTU) – an outline. Inform Sciences 172:1–40
Zadeh LA (2008) Is there a need for fuzzy logic? Inform Sciences 178(13):2751–2779
Zadeh LA (2011) Computing with Words – Principal Concepts and Ideas. Studies in Fuzziness and Soft Computing. Springer, Heidelberg
Zadeh LA (2015) Fuzzy logic – a personal perspective. Fuzzy Set Syst
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
D’Onofrio, S., Portmann, E. Von Fuzzy-Sets zu Computing-with-Words. Informatik Spektrum 38, 543–549 (2015). https://doi.org/10.1007/s00287-015-0920-y
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00287-015-0920-y