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Regularisation Technique for a Distributed Parameter Identification Problem

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  • Joseph Acquah
  • Francis Benyah
  • Jerry S. Y. Kuma

Abstract

This paper examined the problem of ill-posedness of solution in identifying parameters from a given groundwater flow model. The solution approach to the problem was attempted by the method of Parameter Transformation coupled with Tikhonov Regularisation with and without Truncation which has not been explored. Convergence of the method was assessed by the L-Curve criterion. Numerical examples were presented to illustrate the efficiency of the proposed Regularisation Technique. Tikhonov Regularisation with Truncation turns to give a more realistic solution estimates when examined numerically, compared to that of Regularisation without Truncation.

Suggested Citation

  • Joseph Acquah & Francis Benyah & Jerry S. Y. Kuma, 2019. "Regularisation Technique for a Distributed Parameter Identification Problem," Journal of Mathematics Research, Canadian Center of Science and Education, vol. 11(1), pages 64-75, February.
    • Handle: RePEc:ibn:jmrjnl:v:11:y:2019:i:1:p:64
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    References listed on IDEAS

    as
    1. Simon N. Wood, 2004. "Stable and Efficient Multiple Smoothing Parameter Estimation for Generalized Additive Models," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 673-686, January.
    2. Pebesma, Edzer, 2012. "spacetime: Spatio-Temporal Data in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 51(i07).
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    More about this item

    Keywords

    ill-posed problem; parameter transformation; regularization with and without truncation; l-curve;
    All these keywords.

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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