Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/112253
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dc.contributorDepartment of Electrical and Electronic Engineering-
dc.creatorHuang, M-
dc.creatorWu, Z-
dc.creatorHan, X-
dc.date.accessioned2025-04-08T00:43:41Z-
dc.date.available2025-04-08T00:43:41Z-
dc.identifier.issn1742-6588-
dc.identifier.urihttp://hdl.handle.net/10397/112253-
dc.descriptionThe 2nd International Conference on Computer Technology and Information Science 21/06/2024 - 22/06/2024 Onlineen_US
dc.language.isoenen_US
dc.publisherInstitute of Physics Publishingen_US
dc.rightsContent from this work may be used under the terms of the Creative Commons Attribution 4.0 licence (https://creativecommons.org/licenses/by/4.0/). Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.en_US
dc.rightsThe following publication Huang, M., Wu, Z., & Han, X. (2024). Solving inverse boundary value problem of Poisson equation by LS-SVM. Journal of Physics: Conference Series, 2852(1), 012005 is available at https://dx.doi.org/10.1088/1742-6596/2852/1/012005.en_US
dc.titleSolving inverse boundary value problem of Poisson equation by LS-SVMen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume2852-
dc.identifier.doi10.1088/1742-6596/2852/1/012005-
dcterms.abstractIn this paper, a new method based on least squares support vector machines (LS-SVM) is presented for solving the inverse boundary value problem of Poisson equation. The closed form analytical solution is obtained by optimizing the regression parameters. The core problem is to transform the parametric regression problem into a quadratic programming problem. To demonstrate the efficiency of the proposed algorithm, numerical experiments are conducted. The proposed method is found to be feasible for the inverse boundary value problem of Poisson equation.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationJournal of physics. Conference series, 2024, v. 2852, 012005-
dcterms.isPartOfJournal of physics. Conference series-
dcterms.issued2024-
dc.identifier.scopus2-s2.0-85207816941-
dc.relation.conferenceInternational Conference on Computer Technology and Information Science [CTIS]-
dc.identifier.eissn1742-6596-
dc.identifier.artn012005-
dc.description.validate202504 bcrc-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_Scopus/WOSen_US
dc.description.fundingSourceSelf-fundeden_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryCCen_US
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