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Modelling of a surface marine vehicle with kernel ridge regression confidence machine

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dc.contributor.authorMoreno Salinas, David
dc.contributor.authorMoreno, Raul
dc.contributor.authorPereira, Augusto
dc.contributor.authorAranda Almansa, JoaquĆ­n
dc.contributor.authorCruz, Jesus M. de la
dc.date.accessioned2025-03-10T18:30:48Z
dc.date.available2025-03-10T18:30:48Z
dc.date.issued2018-12-27
dc.descriptionThe registered version of this article, first published in Applied Soft Computing, is available online at the publisher's website: Elsevier, https://doi.org/10.1016/j.asoc.2018.12.002
dc.descriptionLa versiĆ³n registrada de este artĆ­culo, publicado por primera vez en Applied Soft Computing, estĆ” disponible en lĆ­nea en el sitio web del editor: Elsevier, https://doi.org/10.1016/j.asoc.2018.12.002
dc.description.abstractThis paper describes the use of Kernel Ridge Regression (KRR) and Kernel Ridge Regression Confidence Machine (KRRCM) for black box identification of a surface marine vehicle. Data for training and test have been obtained from several manoeuvres typically used for marine system identification. Thus, a 20/20 degrees Zig-Zag, a 10/10 degrees Zig-Zag, and different evolution circles have been employed for the computation and validation of the model. Results show that the application of conformal prediction provides an accurate model that reproduces with large accuracy the actual behaviour of the ship with confidence margins that ensure that the model response is within these margins, making it a suitable tool for system identification.en
dc.description.versionversiĆ³n final
dc.identifier.citationDavid Moreno-Salinas, Raul Moreno, Augusto Pereira, Joaquin Aranda, Jesus M. de la Cruz, Modelling of a surface marine vehicle with kernel ridge regression confidence machine, Applied Soft Computing, Volume 76, 2019, Pages 237-250
dc.identifier.doihttps://doi.org/10.1016/j.asoc.2018.12.002
dc.identifier.issn1872-9681
dc.identifier.urihttps://hdl.handle.net/20.500.14468/26209
dc.journal.titleApplied Soft Computing
dc.journal.volume76
dc.language.isoen
dc.page.final250
dc.page.initial237
dc.publisherElsevier
dc.relation.centerE.T.S. de Ingenieros Industriales
dc.relation.departmentInformƔtica y AutomƔtica
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/deed.es
dc.subject1203 Ciencia de los ordenadores
dc.subject.keywordssystem identificationen
dc.subject.keywordsmarine systemsen
dc.subject.keywordsKernel Ridge Regression (KRR)en
dc.subject.keywordsConformal Predictors (CP)en
dc.subject.keywordsKernel Ridge Regression Confidence Machine (KRRCM)es
dc.titleModelling of a surface marine vehicle with kernel ridge regression confidence machineen
dc.typeartĆ­culoes
dc.typejournal articleen
dspace.entity.typePublication
relation.isAuthorOfPublicationcda6ce3d-ab73-4c9e-891f-543c04d8d53b
relation.isAuthorOfPublication3c2f82d3-b350-435d-9954-9321ab17ea9b
relation.isAuthorOfPublication.latestForDiscoverycda6ce3d-ab73-4c9e-891f-543c04d8d53b
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