Szczegóły publikacji
Opis bibliograficzny
A memetic framework for solving difficult inverse problems / Maciej SMOŁKA, Robert SCHAEFER // W: Applications of evolutionary computation : 17th European conference, EvoApplications 2014 : Granada, Spain, April 23—25, 2014 : revised selected papers / eds. Anna I. Esparcia-Alzácar, [et al.]. — Berlin ; Heidelberg : Springer-Verlag, cop. 2014. — (Lecture Notes in Computer Science ; ISSN 0302-9743 ; LNCS 8602). — ISBN: 978-3-662-45522-7; e-ISBN: 978-3-662-45523-4. — S. 138–149. — Bibliogr. s. 148–149, Abstr.
Autorzy (2)
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 87760 |
|---|---|
| Data dodania do BaDAP | 2015-02-12 |
| DOI | 10.1007/978-3-662-45523-4_12 |
| Rok publikacji | 2014 |
| Typ publikacji | materiały konferencyjne (aut.) |
| Otwarty dostęp |  |
| Konferencja | 17th European Conference on Applications of Evolutionary Computation |
| Czasopisma/serie | Lecture Notes in Computer Science, Theoretical Computer Science and General Issues |
Abstract
The paper introduces a multi-deme, memetic global optimization strategy Hierarchic memetic Strategy (HMS) especially well-suited to the solution of a class of parametric inverse problems. This strategy develops dynamically a tree of dependent populations (demes) searching with the various accuracy growing from the root to the leaves. The search accuracy is associated with the accuracy of solving direct problems by hp-adaptive Finite Element Method. Throughout the paper we describe details of exploited accuracy adaptation and computational cost reduction mechanisms, an agent-based architecture of the proposed system, a sample implementation and preliminary benchmark results.
