Revista de Matemática: Teoría y Aplicaciones ISSN Impreso: 1409-2433 ISSN electrónico: 2215-3373

OAI: https://revistas.ucr.ac.cr/index.php/matematica/oai
Algoritmos evolutivos en la solución de problemas de estimación de parámetros
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Keywords

Estimation of parameters problem
dynamical systems
genetic or evolutive algorithm
Estimación de parámetros
modelos dinámicos
algoritmos evolutivos

How to Cite

Marrero Severo, A. de los Ángeles, Pedroso Rodríguez, L. M., & Barrios Ginart, J. (2006). Algoritmos evolutivos en la solución de problemas de estimación de parámetros. Revista De Matemática: Teoría Y Aplicaciones, 13(2), 139–150. https://doi.org/10.15517/rmta.v13i2.276

Abstract

The global problem to determine the values of some parameters in dynamical models knowing experimental results is frequently known as Parameters Estimation Problem and it appears in many areas of sciences. So is clear that there are many ways to obtain a famuly of parametersvalues that satisfy the satated conditions. This work shows some experiences in the treatment of this kind of models when the constraints are ordinary differential equations using evolutive algorithms. Our aim is to show that another ways can be usefull too to solve this problem with similar facilities and efficiency.

https://doi.org/10.15517/rmta.v13i2.276
PDF (Español (España))

References

Bard, J. (1974) Non linear Parameter Estimation. Academic Press Inc.

Butcher, J.C.(1987) The Numerical Analysis of Ordinary Differential Equations. John Wiley, New York.

Dennis, J.E.; Schnabel, R.B. (1983) Numerical Methods for Unconstrained Optimization and Non Linear Equations. Prentice-Hall Series in Computational Mathematics, New Jersey.

Enright, W.H.(1976) “Second derivate multi-step methods for Stiff Ordinary Differential Equations”, Numerical Analysis 2(2).

Gear, W.C.(1971) Numerical Initial Value Problems in ODE. Prentice-Hall, New Jersey.

Gómez, J.A.; Marrero, A. (2000) “Computing gradients of inverse problems in ODE models”, Revista de Investigación Operativa, ALIO 9(1,2,3): 179–206.

Gómez, J.A & Marrero, A. (2000) “Convergence of discrete approximations of inverse problems in ODE models”, Revista Investigación Operativa, ALIO 9(1,2,3): 207–224.

Hairer, E.; Warnner, G.; Nørsett, S.P. (1996) Solving Ordinary Differential Equations I, II. Springer-Verlag, New York.

Holland, J. (1975) Adaptation in Natural and Artificial Systems. Univ. of Michigan Press, Ann Arbor.

Iserles, A. (1996) “A First Course in the Numerical Analysis of Differential Equations”, D.G. Crighton, Univ. of Cambridge.

Jacquez, J.; Greif, P. (1985) “Numerical parameter identifiability and estimability and optimal sampling design”, Math. Biosciences 77.

Luenberger, D.E. (1984) Linear and non linear Programming, Second Edition. Addison-Wesley, Massachusetts.

Marrero, A. (2000) Un Enfoque para la Solución Numérica del Problema de Estimación de Parámetros en Modelos Definidos por Sistemas de Ecuaciones Diferenciales Ordinarias. Tesis Doctoral, Fac. de Mat. Comput, Universidad de La Habana.

Michalewicz, Z.( 1992) Genetic Algorithms + Data Structures = Evolution Programs. Springer-Verlag, Berlin Heidelberg.

Mitsui, T. (1980) “The initial value adjusting method for problems of the least square type of ODE”, Publ. RIMS, University of Kyoto, 16.

Nørsett, S.P.; Wolfbrandt, A. (1979) “Order conditions for Rosenbrock types methods”, Numer.Math 32.

Shampine, L.F.; Reichelt, M.W. (1997) “The Matlab ODE suite”, SIAM J. Sci. Comput, 18(1).

Zedan, H. (1989) “A variable order/variable –stepsize Rosenbrock-type algorithm for solving stiff systems of ODE’s”, Tech. Report YCS114, Dept. Comp. Sci., Univ. of York, England.

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