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Adaptive Algorithms

dc.date.accessioned2019-10-24T15:22:24Z
dc.date.available2019-10-24T15:22:24Z
dc.date.issued2016
dc.identifier.urihttp://publications.mfo.de/handle/mfo/3548
dc.description.abstractOverwhelming empirical evidence in computational science and engineering proved that self-adaptive mesh-generation is a must-do in real-life problem computational partial differential equations. The mathematical understanding of corresponding algorithms concerns the overlap of two traditional mathematical disciplines, numerical analysis and approximation theory, with computational sciences. The half workshop was devoted to the mathematics of optimal convergence rates and instance optimality of the Dörfler marking or the maximum strategy in various versions of space discretisations and time-evolution problems with all kind of applications in the efficient numerical treatment of partial differential equations.
dc.titleAdaptive Algorithms
dc.rights.licenseDieses Dokument darf im Rahmen von § 53 UrhG zum eigenen Gebrauch kostenfrei heruntergeladen, gelesen, gespeichert und ausgedruckt, aber nicht im Internet bereitgestellt oder an Außenstehende weitergegeben werden.de
dc.rights.licenseThis document may be downloaded, read, stored and printed for your own use within the limits of § 53 UrhG but it may not be distributed via the internet or passed on to external parties.en
dc.identifier.doi10.14760/OWR-2016-44
local.series.idOWR-2016-44
local.subject.msc65
local.subject.msc41
local.sortindex988
local.date-range18 Sep - 24 Sep 2016
local.workshopcode1638a
local.workshoptitleAdaptive Algorithms
local.organizersCarsten Carstensen, Berlin; Rob Stevenson, Amsterdam
local.report-nameWorkshop Report 2016,44
local.opc-photo-id1638a
local.publishers-doi10.4171/OWR/2016/44
local.ems-referenceCarstensen Carsten, Stevenson Rob: Adaptive Algorithms. Oberwolfach Rep. 13 (2016), 2513-2570. doi: 10.4171/OWR/2016/44


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