Rule acquisition and adjustment based on set-valued mapping

Information Sciences

Volumn 157, Issue 1-4, 2003, Pages 167-198

  Xu, Yang ^a   Liu, Jun ^b   Ruan, Da ^c  

^a SOUTHWEST JIAOTONG UNIVERSITY   (China)

^b UNIVERSITY OF MANCHESTER   (United Kingdom)

^c BELGIAN NUCLEAR RESEARCH CENTRE   (Belgium)

Author keywords

Fuzzy rule acquisition; Fuzzy rule adjustment; Fuzzy rule representation; Set valued mapping

Indexed keywords

CONFORMAL MAPPING; DATA ACQUISITION; DATA REDUCTION; FUZZY SETS;

SET-VALUED MAPPING;

INFORMATION SCIENCE;

EID: 0242270897     PISSN: 00200255     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0020-0255(03)00188-9     Document Type: Article

References (31)

1. A. Kandel, X.T. Peng, Z.Q. Cao, P.Z. Wang, Representation of concepts by factor spaces, in: Proc. of the Third Int. Fuzzy Systems Association (IFSA) Congress, Seattle, WA (August 6-11), 1989, pp. 145-148.
2. B. De Baets, M. Gupta, E.E. Kerre, Expert knowledge representation by means of piecewise linear fuzzy quantities, in: Proc. of the Third Int. Fuzzy Systems Association Congress, 1989, Seattle, USA, pp. 618-621.
3. B. Everitt, Cluster Analysis, Social Science Research Council, 1974.
4. Kosko B. Neural Networks and Fuzzy Systems. 1992;Prentice-Hall, USA.
5. Luo C.Z. Introduction to Fuzzy Sets. 1989;Beijing Normal University Press. (in Chinese).
6. Nauck D., Kruse R. A neuro-fuzzy method to learn fuzzy classification riles from data. Fuzzy Sets Syst. 89:1997;277-288.
7. Dubois D. Twofold fuzzy sets and rough sets - some issues. Fuzzy Sets Syst. 23:1987;3-18.
8. D. Gustafson, W. Kessel, Fuzzy clustering with a fuzzy covariance matrix, in: Proc. IEEE CDC, San Diego, 1979, pp. 761-766.
9. D. Nauck, R. Kruse, NEFCLASS-a neuro-fuzzy approach for the classification of data, in: K. George, J.H. Carrol, E. Deaton, D. Oppenheim, J. Hightower (Eds.), Applied Computing 1995, in: Proc. of the 1995 ACM Symposium on Applied Computing, ACM Press, New York, 1995, pp. 461-465.
10. E.E. Kerre, Introduction to the basic principles of fuzzy set theory and some of its applications, Commun. Cognit., Blandijnberg 2, 1991.
11. F. Klawonn, D. Nauck, R. Kruse, Generation rule from data by fuzzy and neuro-fuzzy methods, in: Proc. of Fuzzy-Neuro-Systems' 95, Darmsadt, 1995, pp. 223-230.
12. H. Ishibuchi, K. Nozaki, H. Tanaka, Pattern classification by distributed representation of fuzzy rules, in: IEEE International Conference on Fuzzy Systems, San Diego, USA, 1992, pp. 643-650.
13. Buckley J.J., Hayashi Y. Fuzzy neural networks: a survey. Fuzzy Sets Syst. 66:1994;1-13.
14. Wang L.-X., Mendel J.M. Generating fuzzy rules by learning from examples. IEEE Trans. Syst. Man Cyb. 22(6):1992;1414-1427.
15. Yang M.S. A survey of fuzzy clustering. Math. Comput. Modell. 18:1993.
16. Wang P.Z., Sugeno M. The factors field and background structure for fuzzy subsets. Fuzzy Math. 2:1982;45-52. (in Chinese).
17. P.Z. Wang, Factor spaces and knowledge representation, in: J.L. Verdegay, M. Delgado (Eds.), Approximate Reasoning Tools for Artificial Intelligence, Interdisciplinary a systems Research Series, Vol. 96 (Verlag TUV Rheinland, Koln, 1990), pp. 62-79.
18. Wang P.Z. Fuzzy Sets and Random Sets Shadow. 1985;Beijing Normal University Press. (in Chinese).
19. Wang P.Z., Liu X.H. Set-valued statistics. J. Eng. Math. 1(1):1984;43-54.
20. Wang P.Z., Liu X.H., Sanchez E. Set-valued statistics and its application to earthquake engineering. Fuzzy Sets Syst. 18:1986;347-356.
21. Liang Ping, Song Fengming What does a probabilistic interpretation of fuzzy sets mean? IEEE Trans. Fuzzy Syst. 4(2):1996;200-205.
22. Martin-Clouaire R., Prade H. On the problem of representation and propagation of uncertainty in expert systems. Int. J. Man-Mach. Stud. 22:1985;119-129.
23. LeFaive R.A. The representation of fuzzy knowledge. J. Cyb. 4:1974;57-66.
24. Abe S., Lan M.-S. A method for fuzzy rules extraction directly from numerical data and its application to pattern classification. IEEE Trans. Fuzzy Syst. 3:1995;18-28.
25. Abe S., Lan M.-S., Thawonmas R. Tuning of a fuzzy classifier derived from data. Int. J. Approx. Reason. 14:1996;1-24.
26. Abe S., Lan M.-S. Fuzzy rules extraction directly from numerical data for function approximation. IEEE Trans. Syst. Man Cyb. 25(1):1995;119-129.
27. S.K. Pal, D.D. Majumdar, Fuzzy Mathematical Approach to Pattern Recognition, New York, 1986.
28. Zhang W.X., Leung Yee The Uncertainty Reasoning Principles. 1996;Xi'an Jiaotong University Press. (in Chinese).
29. Zou K.Q., Xu Y. Fuzzy Systems and Expert Systems. 1989;Southwest Jiaotong University Press. (in Chinese).
30. Xu Y., Kerre E.E., Ruan D., Song Z.M. Fuzzy reasoning based on the extension principle. Int. J. Intell. Syst. 16(4):2001;469-495.
31. Y. Xu, E.E. Kerre, D. Ruan, Z.M. Song, A study on fuzzy reasoning mechanism based on extension principle, in: Proc. of the Ninth IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2000): Soft Computing in the Information Age, San Antonio, Texas, USA, May 7-8, 2000.