Interval-valued GA-P algorithms

IEEE Transactions on Evolutionary Computation

Volumn 4, Issue 1, 2000, Pages 64-72

  Sánchez, Luciano ^a  

^a UNIVERSITY OF OVIEDO   (Spain)

Author keywords

[No Author keywords available]

Indexed keywords

APPROXIMATION THEORY; FUZZY SETS; MATHEMATICAL MODELS; MATHEMATICAL PROGRAMMING; NEURAL NETWORKS; REGRESSION ANALYSIS;

GENETIC PROGRAMMING (GP);

GENETIC ALGORITHMS;

EID: 0033740103     PISSN: 1089778X     EISSN: None     Source Type: Journal    
DOI: 10.1109/4235.843495     Document Type: Article

References (24)

1. D. Adler, "Genetic algorithms and simulated annealing: A marriage proposal," in Proc. IEEE Int. Conf. Neural Networks, vol. 2, 1993, pp. 1104-1109.
2. P. Billingsley, Probability and Measure. New York: Wiley Ser. in Prob, and Math. Statist., 1995.
3. I. Couso, "La envolvente probabilística. Definición y propiedades," trabajo de investigación, Departamento de Estadística e I.O y D.M., Univ. Oviedo, Spain, 1997.
4. O. Cordón, "A general study on genetic fuzzy systems," in Genetic Algorithms in Engineering and Computer Science, J. Periaux, G. Winter, M. Galn, and P. Cuesta, Eds. New York: Wiley, 1995, pp. 33-57.
5. _, "Una metodologiá para el diseño automático de sistemas basados en reglas difusas mediante algoritmos evolutives," doctoral dissertation, Departamento de Cieneias de la Computación e Inteligencia Artificial, Univ. Granada, Spain, 1997.
6. A. P. Dempster, "Upper and lower probabilities generated by a random closed interval," Ann. Math. Statist., vol. 38, pp. 325-339, 1967.
7. C. Fonseca and P. J. Fleming, "An overview of evolutionary algorithms in multiobjective optimization," Evol. Comput., vol. 3, pp. 1-16, 1995.
8. L. Howard and D. D'Angelo, "The GA-P: A genetic algorithm and genetic programming hybrid," IEEE Expert, pp. 11-15, June 1995.
9. W. Härdle, Applied Nonparametric Regression. Cambridge, U.K.: Cambridge Univ. Press, 1989.
10. H. Iba, T. Sato, and H. De Garis, "System identification approach to genetic programming," in Proc. 1st IEEE Conf. Evol. Comput., vol. 1, 1994, pp. 401-406.
11. H. Ishibuchi, H. Tanaka, and H. Okada, "An architecture of neural networks with interval weights and its application to fuzzy regression analysis," Fuzzy Sets Syst., vol. 57, pp. 27-39, 1993.
12. L. Kacprzyk and M. Fedrizzi, Eds., Fuzzy Regression Analysis. Warsaw, Poland: Omnitech, 1984.
13. A. Kaufmann and M. Gupta, Eds., Introduction to Fuzzy Arithmetic. New York: Van Nostrand Reinhold, 1984.
14. J. Koza, Genetic Programming. On the Programming of Computers by Means of Natural Selection. Cambridge, MA: M.I.T. Press, 1992.
15. C. G. Looney, Pattern Recognition Using Neural Networks. Theory and Algorithms for Engineers and Scientists. Oxford, U.K.: Oxford Univ. Press, 1997.
16. G. Matheron, Random Sets and Integral Geometry. New York: Wiley Ser. Prob, and Math. Statist., 1975.
17. B. Lindgren, Statistical Theory. London, U.K.: Chapman & Hall, 1993.
18. Z. Michaliewicz, Genetic Algorithms + Data Structures = Evolution Programs. Berlin, Germany: Springer-Verlag, 1992.
19. J. M. Renders and H. Bersini, "Hybridizing genetic algorithms with hill-climbing methods for global optimization: Two possible ways," in Proc. 1st IEEE Conf. Evol. Comput., vol. 1, 1994, pp. 312-317.
20. J. M. Renders and S. P. Flasse, "Hybrid methods using genetic algorithms for global optimization," IEEE Trans. Syst., Man, Cybern. - Part B: Cybern., vol. 26, Apr. 1996.
21. R. Rojas, Neural Networks - A Systematic Introduction. Berlin, Germany: Springer-Verlag, 1996.
22. L. Sánchez, "A random sets based method for identifying fuzzy models," Fuzzy Sets Syst., vol. 3, pp. 343-354, 1998.
23. G. Shafer, A Mathematical Theory of Evidence. Princeton, NJ: Princeton Univ. Press, 1976.
24. T. Takagi and M. Sugeno, "Fuzzy identification of systems and its application to modeling and control," IEEE Trans. Syst., Man, Cybern., vol. SMC-15, no. 1, pp. 116-132, 1985.