Abstract
Many propositions about the real world are not either true or false, rendering classical logic inadequate for reasoning with such propositions. Furthermore, most concepts used in human communication do not have crisp boundaries, rendering classical sets inadequate to represent such concept. The main aim of fuzzy logic and fuzzy sets is to overcome the disadvantages of classical logic and classical sets.
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References
J.C. Bezdek. Fuzzy Models—What Are They, and Why? IEEE Trans. on Fuzzy Systems 1:1–5. IEEE Press, Piscataway, NJ, USA, 1993
D. Butnariu and E.P. Klement. Triangular Norm-based Measures and Games with Fuzzy Coalitions. Kluwer, Dordrecht, Netherlands, 1993
S. Gottwald (ed.) A Treatise on Many-Valued Logic. Research Studies Press, Baldock, UK, 2003
R. Kruse, J. Gebhardt, and F. Klawonn. Foundations of Fuzzy Systems. J. Wiley & Sons, Chichester, United Kingdom, 1994
A. Mayer, B. Mechler, A. Schlindwein and R. Wolke. Fuzzy Logic. Addison-Wesley, Bonn, Germany, 1993
L.A. Zadeh. Fuzzy Sets. Information and Control 8(3):338–353, 1965
H.-J. Zimmermann and P. Zysno. Latent Connectives in Human Decision Making and Expert Systems. Fuzzy Sets and Systems 4:37–51. Elsevier, Amsterdam, Netherlands, 1980
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Kruse, R., Borgelt, C., Klawonn, F., Moewes, C., Steinbrecher, M., Held, P. (2013). Fuzzy Sets and Fuzzy Logic. In: Computational Intelligence. Texts in Computer Science. Springer, London. https://doi.org/10.1007/978-1-4471-5013-8_15
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DOI: https://doi.org/10.1007/978-1-4471-5013-8_15
Publisher Name: Springer, London
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