Fuzzy rule base learning through simulated annealing

Fuzzy Sets and Systems

Volumn 105, Issue 3, 1999, Pages 353-363

  Guély, Francois ^a,b   La, Rémy ^a,b   Siarry, Patrick ^a  

^a ECOLE CENTRALE PARIS   (France)

^b SCHNEIDER ELECTRIC   (France)

Author keywords

[No Author keywords available]

Indexed keywords

APPROXIMATION THEORY; COMPUTATIONAL COMPLEXITY; CONVERGENCE OF NUMERICAL METHODS; MEMBERSHIP FUNCTIONS; SIMULATED ANNEALING;

FUZZY RULE LEARNING; TAKAGI-SUGENO RULES;

FUZZY SETS;

EID: 0344614423     PISSN: 01650114     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0165-0114(97)00260-1     Document Type: Article

References (17)

1. [1] E.H.L. Aarts, P.J.M. Van Laarhoven, Simulated Annealing: Theory and Applications, Reidel, Dordrecht, 1987.
2. [2] V. Cerny, Thermodynamical approach to the traveling salesman problem: an efficient simulation algorithm, J. Optim. Theory Appl. 45 (1), (1985).
3. [3] A. Corana, M. Marchesi, C. Martini, S. Ridella, Minimizing multimodal functions of continuous variables with the simulated annealing algorithm, ACM Trans. Math. Software 13 (1987) 262-280.
4. [4] F. Guély, P. Siarry, Gradient descent method for optimizing various fuzzy rule bases, Proc. 2nd IEEE Internat. Conf. on Fuzzy Systems FUZZ-IEEE '93, San Francisco CA, vol. 2, March 1993, pp. 1241-1246.
5. [5] F. Guély, P. Siarry, A centred formulation of Takagi-Sugeno rules for improved learning efficiency, Fuzzy Sets and Systems 62 (1994) 277-285.
6. [6] H. Ichihashi, Iterative fuzzy modeling and a hierarchical network, in: Proc. IFSA '91 Bruxelles, Vol. Engineering, 1991, pp. 49-52.
7. [7] S. Isaka, A.V. Sebald, A. Karimi, N.T. Smith, M.L. Quinn, On the design and performance evaluation of adaptive fuzzy controllers, in: Proc. IEEE '88 Conf. on Decision and Control, Austin, TX, vol. 2, 1988, pp. 1068-1069.
8. [8] J.S.R. Jang, Fuzzy controller design without domain experts, in: Proc. 1st IEEE Internat. Conf. on Fuzzy Systems FUZZ IEEE '92, San Diego, 1992, pp. 289-296.
9. [9] C.L. Karr, E.J. Gentry, Fuzzy control of pH using genetic algorithms, IEEE Trans. Fuzzy Systems (1) (February 1993).
10. [10] S. Kirkpatrick, C.D. Gelatt, M.P. Vecchi, Optimization by simulated annealing, Science 220 (1983) 671-680.
11. [11] M.A. Lee, H. Takagi, Integrated design stages of fuzzy systems using genetic algorithms, in: Proc. 2nd IEEE Internat. Conf. on Fuzzy Systems FUZZ-IEEE '93, San Francisco, March 1993, pp. 612-617.
12. [12] H. Nomura, I. Hayashi, N. Wakami, A self-tuning method of fuzzy control by descent method, in: Proc. IFSA '91 Bruxelles, Vol. Engineering, 1991, pp. 155-158.
13. [13] T.J. Procyk, E.H. Mamdani, A linguistic self-organizing process controller, Automatica 15 (1979) 15-30.
14. [14] P. Siarry, G. Dreyfus, La Méthode du Recuit Simulé: Théorie et Applications, I.D.S.E.T. (E.S.P.C.I.), Paris, 1988.
15. [15] P. Siarry, F. Guély, A genetic algorithm for optimizing Takagi-Sugeno fuzzy rule bases, Fuzzy Sets and Systems (to be published).
16. [16] M. Sugeno, T. Takagi, Fuzzy identification of systems and its applications to modeling and control, IEEE Trans. Systems Man Cybernet. SMC-15(1) (January/February 1985) 116-132.
17. [17] T. Takagi, M. Sugeno, Derivation of fuzzy control rules from human operator's control actions, in: Proc. Internat. Fuzzy Association Conf. IFAC '83.