Fuzzy rule extraction by a hybrid GA and SVD-QR method for pattern classification

International Journal of Electrical Engineering

Volumn 12, Issue 2, 2005, Pages 113-123

  Wong, Ching Chang ^a   Lin, Bo Chen ^a   Chen, Chia Chong ^b  

^a TAMKANG UNIVERSITY   (Taiwan)

^b WUFENG INSTITUTE OF TECHNOLOGY   (Taiwan)

Author keywords

Fuzzy system; Genetic algorithms; Pattern classification; SVD QR method

Indexed keywords

ELECTRICAL ENGINEERING; GENETIC ALGORITHMS; MATHEMATICAL TRANSFORMATIONS; MEMBERSHIP FUNCTIONS; PATTERN RECOGNITION;

FUZZY RULES; FUZZY SYSTEMS; SVD-QR METHOD; TRANSFORMATION TECHNIQUES;

FUZZY SETS;

EID: 24144475960     PISSN: 18123031     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (31)

1. S. Abe and M. S. Lan, "Fuzzy rules extraction directly from numerical data for function approximation," IEEE Trans. on Systems, Man and Cybernetics, vol. 25, no. 1, pp. 119-129, Jan. 1995.
2. S. L. Chiu, "A cluster estimation method with extension to fuzzy model identification," in Proc. IEEE Int. Conf. on Fuzzy Systems, vol. 2, San Diego, CA, June 1994, pp. 1240-1245.
3. O. Cordón, F. Herrera, and P. Villar, "Generating the knowledge base of a fuzzy rule-based system by the genetic learning of the data base," IEEE Trans. on Fuzzy Systems, vol. 9, no. 4, pp. 667-674, Aug. 2001.
4. L. Davis (Ed.), Handbook of Genetic Algorithms, New York: Van Nostrand Reinhold, 1991.
5. J. Demmel and K. Veselic, Jacobi's method is more accurate than QR, Technical Report, UT-CS-89-88, Oct. 1989.
6. R. A. Fisher, "The use of multiple measurements in taxonomic problems," Annals of Eugenics, vol. 7, no. 2, pp. 179-188, 1936.
7. D. E. Goldberg, Genetic Algorithms in Search, Optimization, and Machine Learning, New York: Addison-Wesley, 1989.
8. G. H. Golub, "Numerical methods for solving least squares problems," Numerical Mathematics, no. 7, pp. 206-216, 1965.
9. G. H. Golub and C. F. Van Loan, Matrix Computations, Baltimore: Johns Hopkins Univ. Press, 1989.
10. M. R. Hestenes, "Inversion of matrices by biorthogonalization and related results," J. Soc. Indust. Appl Math., vol. 6, no. 1, pp. 51-90, 1958.
11. H. Ishibuchi, K. Nozaki, and H. Tanaka, "Distributed representation of fuzzy rules and its application to pattern classification," Fuzzy Sets and Systems, vol. 52, no. 1, pp. 21-32, Nov. 1992.
12. H. Ishibuchi, K. Nozaki, N. Yamamoto, and H. Tanaka, "Selecting fuzzy if-then rules for classification problems using genetic algorithms," IEEE Trans. on Fuzzy Systems, vol. 3, no. 3, pp. 260-270, Aug. 1995.
13. C. L. Karr, "Applying genetics to fuzzy logic," AI Expert, vol. 6, no. 3, pp.38-43, Mar. 1991.
14. M. A. Lee and H. Takagi, "Integrating design stages of fuzzy systems using genetic algorithms," in Proc. IEEE Int. Conf. on Fuzzy Systems, vol. 1, San Francisco, CA, Apr. 1993, pp. 612-617.
15. P. A. Mastorocostas, J. B. Theocharis, and V. S. Petridis, "A constrained orthogonal least-squares method for generating TSK fuzzy models: application to short-term load forecasting," Fuzzy Sets and Systems, vol. 118, no. 2, pp. 215-233, Mar. 2001.
16. G. C. Mouzouris and J. M. Mendel, "Designing fuzzy logic systems for uncertain environments using a singular-value-QR decomposition method," in Proc. IEEE Int. Conf. on Fuzzy Systems, vol. 1, New Orleans, LA, Sept. 1996, pp. 295-301.
17. H. Nomura, I. Hayashi, and N. Wakami, "A self-tuning method of fuzzy reasoning by genetic algorithm," in Proc. Int. Conf. on Fuzzy Systems and Intelligent Control, Louisville, KY, Mar. 1992, pp. 236-245.
18. M. Russo, "Genetic Fuzzy Learning," IEEE Trans. on Evolutionary Computation, vol. 4, no. 3, pp. 259-273, Sept. 2000.
19. M. Seines and R. Babuska, "Rule base reduction: Some comments on the use of orthogonal transforms," IEEE Trans. on Systems, Man and Cybernetic, vol. 31, no. 2, pp. 199-206, May 2001.
20. G. W. Stewart, "Rank degeneracy," SIAM J. Sci. Statist. Comput., vol. 5, no. 2, pp. 403-413, 1984.
21. M. Sugeno and T. Yasukawa, "A fuzzy-logic-based approach to qualitative modeling," IEEE Trans. on Fuzzy Systems, vol. 1, no. 1, pp. 7-31, Feb. 1993.
22. T. Takagi and M. Sugeno, "Fuzzy identification of systems and its applications to modeling and control," IEEE Trans. on Systems, Man and Cybernetics, vol. 15, no. 1, pp. 116-132, Feb. 1985.
23. L. X. Wang and J. M. Mendel, "Generating fuzzy rules by learning from examples," IEEE Trans. on Systems, Man and Cybernetics, vol. 22, no. 6, pp. 1414-1427, Nov.-Dec. 1992.
24. C. C. Wong and C. C. Chen, "A hybrid clustering and gradient descent approach for fuzzy modeling," IEEE Trans. on Systems, Man and Cybernetics, vol. 29, no. 6, pp. 686-693, Dec. 1999.
25. C. C. Wong, B. C. Lin and C. C. Chen, "Fuzzy system design by a GA-based method for data classification," Cybernetics and Systems, vol. 33, no. 3, pp. 253-270, Apr.-May 2002.
26. R. R. Yager and D. P. Filev, Essentials of Fuzzy Modeling and Control, New York: John Wiley, 1994.
27. Y. Yam, "Fuzzy approximation via grid point sampling and singular value decomposition," IEEE Trans. on Systems, Man and Cybernetic, vol. 27, no. 6, pp, 933-951, Dec. 1997.
28. Y. Yam, P. Baranyi, and C. T. Yang, "Reduction of fuzzy rule bases via singular value decomposition," IEEE Trans. on Fuzzy Systems, vol. 7, no. 2, pp. 120-132, Apr. 1999.
29. J. Yen and L. Wang, "An SVD-based fuzzy model reduction strategy," in Proc. IEEE Int. Conf. on Fuzzy Systems, vol. 2, New Orleans, LA, Sept. 1996, pp. 835-841.
30. J. Yen and L. Wang, "Application of statistical information criteria for optimal fuzzy model construction," IEEE Trans. on Fuzzy Systems, vol. 6, no. 3, pp. 362-372, Aug. 1998.
31. J. Yen and L. Wang, "Simplifying fuzzy rule-based models using orthogonal transformation methods," IEEE Trans. on Systems, Man and Cybernetics, vol. 29, no. 1, pp. 13-24, Feb. 1999.