dc.contributor.author | Stasik, Alexander Johannes | |
dc.contributor.author | Sterud, Camilla | |
dc.contributor.author | Bøhn, Eivind Eigil | |
dc.contributor.author | Riemer-Sørensen, Signe | |
dc.date.accessioned | 2023-02-21T14:37:36Z | |
dc.date.available | 2023-02-21T14:37:36Z | |
dc.date.created | 2023-02-15T12:39:31Z | |
dc.date.issued | 2023 | |
dc.identifier.citation | Physica D : Non-linear phenomena. 2023, 446, 133673. | en_US |
dc.identifier.issn | 0167-2789 | |
dc.identifier.uri | https://hdl.handle.net/11250/3052840 | |
dc.description.abstract | Hybrid machine learning based on Hamiltonian formulations has recently been successfully demonstrated for simple mechanical systems, both energy conserving and not energy conserving. We introduce a pseudo-Hamiltonian formulation that is a generalization of the Hamiltonian formulation via the port-Hamiltonian formulation, and show that pseudo-Hamiltonian neural network models can be used to learn external forces acting on a system. We argue that this property is particularly useful when the external forces are state dependent, in which case it is the pseudo-Hamiltonian structure that facilitates the separation of internal and external forces. Numerical results are provided for a forced and damped mass–spring system and a tank system of higher complexity, and a symmetric fourth-order integration scheme is introduced for improved training on sparse and noisy data. | en_US |
dc.language.iso | eng | en_US |
dc.publisher | Elsevier | en_US |
dc.rights | Navngivelse 4.0 Internasjonal | * |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/deed.no | * |
dc.title | Pseudo-Hamiltonian neural networks with state-dependent external forces | en_US |
dc.title.alternative | Pseudo-Hamiltonian neural networks with state-dependent external forces | en_US |
dc.type | Peer reviewed | en_US |
dc.type | Journal article | en_US |
dc.description.version | publishedVersion | en_US |
dc.rights.holder | © 2023 The Author(s) | en_US |
dc.source.volume | 446 | en_US |
dc.source.journal | Physica D : Non-linear phenomena | en_US |
dc.identifier.doi | 10.1016/j.physd.2023.133673 | |
dc.identifier.cristin | 2126287 | |
dc.source.articlenumber | 133673 | en_US |
cristin.ispublished | true | |
cristin.fulltext | original | |
cristin.qualitycode | 2 | |