Data Assimilation and Parameter Identification for Water Waves Using the Nonlinear Schrödinger Equation and Physics-Informed Neural Networks

dc.contributor.authorSvenja Ehlers
dc.contributor.authorNiklas A. Wagner
dc.contributor.authorAnnamaria Scherzl
dc.contributor.authorMarco Klein
dc.contributor.authorNorbert Hoffmann
dc.contributor.authorMerten Stender
dc.date.accessioned2025-04-16T12:49:13Z
dc.date.available2025-04-16T12:49:13Z
dc.identifier.urihttps://tustorage.ulb.tu-darmstadt.de/handle/tustorage/18498
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subject.ddc530
dc.titleData Assimilation and Parameter Identification for Water Waves Using the Nonlinear Schrödinger Equation and Physics-Informed Neural Networks
dc.typesupplierxml
dspace.entity.typeDistribution
relation.isDatasetOfDistributionc3267634-96b9-49c7-9b4d-af48a7ed8176
relation.isDatasetOfDistribution.latestForDiscoveryc3267634-96b9-49c7-9b4d-af48a7ed8176

Files

Original bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
fluids-09-10-00231.xml
Size:
288.88 KB
Format:
Extensible Markup Language

Collections