







References
Ding L, Shen Z, Mukaidono M (1992) Revision principle for approximate reasoning—based on linear revising method. In: Iizuka ’92, pp 305–308
Dubois D, Grabisch M, Prade H (1992) Gradual rules and the approximation of functions. In: Iizuka ’92, pp 629–632
Kóczy LT, Hirota K (1993a) Ordering, distance and closeness of fuzzy sets. Fuzzy Sets Syst 59:281–293
Kóczy LT, Hirota K (1993b) Approximate reasoning by linear rule interpolation and general approximation. Int J Approx Reason 9:197–224
Mamdani EH, Assilian S (1975) An experiment in linguistic synthesis with a fuzzy logic controller. Int J Man Mach Stud 7:1–13
Mizumoto M, Zimmermann HJ (1982) Comparison of fuzzy reasoning methods. Fuzzy Sets Syst 8:253–283
Türkşen IB, Zhong Z (1988) An approximate analogical reasoning approach based on similarity measures. IEEE Trans Syst Man Cybern 16:1049–1056
Zadeh LA (1965) Fuzzy sets. Inform Control 8:338–353
Zadeh LA (1973) Outline of a new approach to the analysis of complex systems and decision processes. IEEE Trans Syst Man Cybern 1:28–44
Acknowledgements
Research supported by the following grants: National Scientific Research Fund OTKA T034233, T034212 and F30056, Info-Communication Technologies and Applications Fund IKTA 207/2001, National Research and Development Projects Fund NKFP-2/15/2002, Ministry of Education FKFP 180/2001.
Author information
Authors and Affiliations
Corresponding author
Additional information
This paper is part of the focus on “Philosophy of Soft Computing” appeared on Volume 8 Number 10 in November 2004
Rights and permissions
About this article
Cite this article
Kóczy, L.T. Fuzziness and computational intelligence: dealing with complexity and accuracy. Soft Comput 10, 178–184 (2006). https://doi.org/10.1007/s00500-005-0470-3
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00500-005-0470-3