Szczegóły publikacji
Opis bibliograficzny
Local misfit approximation in memetic solving of ill-posed inverse problems / Marcin ŁOŚ, Robert SCHAEFER, Jakub SAWICKI, Maciej SMOŁKA // W: Applications of evolutionary computation : 20th European conference, EvoApplications 2017 : Amsterdam, The Netherlands, April 19–21, 2017 : proceedings, Pt. 1 / eds. Giovanni Squillero, [et al.]. — Switzerland : Springer International Publishing, cop. 2017. — (Lecture Notes in Computer Science ; ISSN 0302-9743 ; LNCS 10199). — ISBN: 978-3-319-55848-6; e-ISBN: 978-3-319-55849-3. — S. 297–309. — Bibliogr. s. 308–309, Abstr. — Publikacja dostępna online od: 2017-03-25
Autorzy (4)
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 105206 |
|---|---|
| Data dodania do BaDAP | 2017-05-15 |
| DOI | 10.1007/978-3-319-55849-3_20 |
| Rok publikacji | 2017 |
| Typ publikacji | materiały konferencyjne (aut.) |
| Otwarty dostęp |  |
| Wydawca | Springer |
| Konferencja | 20th European conference on Applications of Evolutionary Computation |
| Czasopisma/serie | Lecture Notes in Computer Science, Theoretical Computer Science and General Issues |
Abstract
The approximation of the objective function is a well known method of speeding up optimization process, especially if the objective evaluation is costly. This is the case of inverse parametric problems formulated as global optimization ones, in which we recover partial differential equation parameters by minimizing the misfit between its measured and simulated solutions. Typically, the approximation used to build the surrogate objective is rough but globally applicable in the whole admissible domain. The authors try to carry out a different task of detailed misfit approximation in the regions of low sensitivity (plateaus). The proposed complex method consists of independent C0C0 Lagrange approximation of the misfit and its gradient, based on the nodes obtained during the dedicated memetic process, and the subsequent projection of the obtained components (single or both) on the space of B-splines. The resulting approximation is globally C1C1 , which allows us to use fast gradient-based local optimization methods. Another goal attained in this way is the estimation of the shape of plateau as an appropriate level set of the approximated objective. The proposed strategy can be applied for solving ill-conditioned real world inverse problems, e.g., appearing in the oil deposit investigation. We show the results of preliminary tests of the method on two benchmarks featuring convex and non-convex U-shaped plateaus.