Memetic approach for irremediable ill-conditioned parametric inverse problems*

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Abstract

The paper introduces a new taxonomy of ill-posed parametric inverse problems, formulated as global optimization ones. It systematizes irremediable problems, which appear quite often in the real life but cannot be solved using the regularization method. The paper also shows a new way of solving irremediable inverse problems by a complex memetic approach including: genetic computation with adaptive accuracy, random sample clustering and a sophisticated local approximation of misfit plateau regions. Finally, we use a benchmark function featuring cross-shaped plateau to discuss some factors that influence the quality of plateau shape approximation.

Keywords

ill-posed inverse problems
plateau shape approximation

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*

The work presented in this paper has been partially supported by Polish National Science Center grants no. DEC-2015/17/B/ST6/01867 and by the AGH statutory research grant no. 11.11.230.124.