A fuzzy theory refinement algorithm

International Journal of Approximate Reasoning

Volumn 19, Issue 3-4, 1998, Pages 193-220

  Gonzalez, Antonio ^a   Perez, Raúl ^a  

^a UNIVERSITY OF GRANADA   (Spain)

Author keywords

Fuzzy logic; Fuzzy rules refinement; Machine learning

Indexed keywords

EID: 0347877230     PISSN: 0888613X     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0888-613X(98)00013-9     Document Type: Article

References (26)

1. P.P. Bonissone, Fuzzy logic controllers: An industrial reality, Computational Intelligence: Imitating Life, IEEE Press, New York, 1994, pp. 316-327.
2. L. Breiman, J.H. Friedman, R.A. Olshen, C.J. Stone, Classification and Regression Trees, Wadsworth, Belmont, CA, 1984.
3. O. Cordón, F. Herrera, A three-stage process for learning descriptive and approximative fuzzy logic controller knowledge bases from examples, Internat. J. Approx. Reas. 17 (1997) 369-407.
4. D. Fensel, M. Wiese, Refinement of rule sets with JoJo, Lectures Notes in Artificial Intelligence 667 (1993) 378-383.
5. D. Driankov, H. Hellendoorn, M. Reinfrank, An Introduction to Fuzzy Control, Springer, Berlin, 1993.
6. R.A. Fisher, The use of multiple measurements in taxonomic problems, Annual Eugenics 7 (1936) 179-188.
7. A. González, R. Pérez, J.L. Verdegay, Learning the structure of a fuzzy rule: A genetic approach, Proceedings of the EUFIT'93, vol. 2, 1993, pp. 814-819; also Fuzzy System and Artificial Intelligence 3 (1) (1994) 57-70.
8. A. González, R. Pérez, J.L. Verdegay, Learning the structure of a fuzzy rule: A genetic approach, Proceedings of the EUFIT'93, vol. 2, 1993, pp. 814-819; also Fuzzy System and Artificial Intelligence 3 (1) (1994) 57-70.
9. A. González, R. Pérez, Structural learning of fuzzy rules from noisy examples, Proceedings of the FUZZIEEE/IFES'95, Yokohama, vol. III, 1995, pp. 1323-1330.
10. A. González, R. Pérez, Completeness and Consistency conditions for learning fuzzy rules, Technical Report #DECSAI-95103, 1995 (to appear in Fuzzy Sets and Systems).
11. A. González, R. Pérez, Refining the rules obtained by SLAVE, Technical Report #DECSAI-95138, 1995.
12. A. González, R. Pérez, A learning system of fuzzy control rules, in: F. Herrera, J.L. Verdegay (Eds.), Genetic Algorithms and Soft Computing, Physica-Verlag, Wuezburg, 1996, pp. 202-225.
13. A. González, R. Pérez, A refinement algorithm of fuzzy rules for classification problems, Proceedings of the IPMU'96, vol. 2, 1996, pp. 533-538.
14. A. González, F. Herrera, Multi-stage genetic fuzzy systems based on the iterative rule learning approach (to appear in Math ware and Soft Computing).
15. A. González, R. Pérez, Aplicación de un Sistema de Refinamiento de Reglas a Problemas de Clasificación, Memoria del V Congreso Iberoamericano de Inteligencia Artificial, Editorial Limusa, 1996, pp. 20-29.
16. H. Hellendoorn, D. Driankow, M. Reinfrank, An introduction to Fuzzy Control, Springer, Berlin, 1993.
17. C.C. Lee, Fuzzy logic in control systems: Fuzzy logic controller, Parts I and II, IEEE Transactions on Systems, Man and Cybernetics 20 (1990) 404-435.
18. E.H. Mamdani, S. Assilian, An experiment in linguistic synthesis with a fuzzy logic controller, International Journal of Man-Machine Studies 7 (1975) 1-13.
19. R.S. Michalski, A theory and methodology of inductive reasoning, in: R.S. Michalski, J. Carbonell, T. Mitchel (Eds.), Machine Learning: An artificial intelligence approach, vol. 1, Morgan Kaufmann, Los Altos, CA, 1984, pp. 83-134.
20. D. Ourston, R.J. Mooney, Theory refinement combining analytical and empirical methods, Artificial Intelligence 66 (1994) 273-309.
21. J.R. Quinlan, Induction of decision trees, Machine learning 1 (1) (1986) 81-106.
22. J.R. Quinlan, C4.5 Program for Machine Learning, Morgan Kaufmann, Los Altos, CA, 1993.
23. S.B. Thrun et al., The monk's problems: A performance comparison of different learning algorithms, Technical Report CMU-CS-91-197, Computer Science Department, Carnegi Mellon University, Pittsburgh, 1991.
24. G. Venturini, SIA: a Supervised Inductive Algorithm with Genetic Search for Learning Attributes based Concepts, Machine Learning: ECML-93, 1993, pp. 280-296.
25. L. Wang, M. Mendel, Generating fuzzy rules by learning from examples, IEEE Transactions on systems, man and cybernetics 22 (6) (1992) 1414-1427.
26. L.A. Zadeh, Fuzzy set, Information and Control 8 (1965) 338-353.