Parameter Estimation in Size/Age Structured Population Models Using the Moving Finite Element Method

  • Gabriel Dimitriu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2542)


We consider the problem of estimating variable parameters in models describing the evolution in time of populations in which individual size or age are taken into account. Our approach uses a Galerkin technique on a non uniform and time dependent grid for the numerical solution of the equation. A moving finite element method which combines the method of characteristics with finite element techniques is applied. Numerical results to an example problem are presented.


Parameter Estimation Problem Linear Spline Structure Population Model Dimensional Linear Subspace Galerkin Technique 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Banks, H. T.: Computational techniques for inverse problems in size-structured stochastic population models. In: Bermudez, A. (ed.): Proc. IFIP Conf. on Optimal Control of Systems Governed by PDE (Santiago de Compostela, July 6-9, 1987). Lecture Notes in Control and Info. Sci., Vol. 114 (1989) 3–10.Google Scholar
  2. 2.
    Banks, H. T. and Kunisch, K.: Estimation Techniques for Distributed Parameter Systems. Progress in Systems and Control, 1, Birkhauser, Boston (1989)Google Scholar
  3. 3.
    Banks, H. T., Tran, H. T., and Woodward, D. E.: Estimation of variable coefficients in the Fokker-Planck equations using moving finite elements. CAMS 90-9, August (1990)Google Scholar
  4. 4.
    Dimitriu, G.: Numerical approximation of the optimal inputs for an identification problem. Intern. J. Computer Math. 70 (1998) 197–209.zbMATHCrossRefMathSciNetGoogle Scholar
  5. 5.
    Harrison, G. W.: Numerical solution of the Fokker-Planck equation using moving finite elements. Numerical Methods for Partial Differential Equations, 4 (1988) 219–232.zbMATHCrossRefMathSciNetGoogle Scholar
  6. 6.
    Lions, J. L.: Optimal Control of Systems Governed by Partial Differential Equations. Springer Verlag, New York (1971)zbMATHGoogle Scholar
  7. 7.
    Schultz, M. H: Spline Analysis. Prentice-Hall, Englewood Cliffs (1973)zbMATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Gabriel Dimitriu
    • 1
  1. 1.Department of Mathematics and InformaticsUniversity of Medicine and Pharmacy, Faculty of PharmacyIasiRomania

Personalised recommendations