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dc.contributor.authorKong, Ling-Wei
dc.contributor.authorFan, Hua-Wei
dc.contributor.authorGrebogi, Celso
dc.contributor.authorLai, Ying-Cheng
dc.date.accessioned2021-01-29T14:02:01Z
dc.date.available2021-01-29T14:02:01Z
dc.date.issued2021-01-28
dc.identifier.citationKong , L-W , Fan , H-W , Grebogi , C & Lai , Y-C 2021 , ' Machine learning prediction of critical transition and system collapse ' , Physical Review Research , vol. 3 , no. 1 , 013090 . https://doi.org/10.1103/PhysRevResearch.3.013090en
dc.identifier.issn2643-1564
dc.identifier.otherPURE: 186549781
dc.identifier.otherPURE UUID: 91a9f680-0eb5-4199-b320-933ee2923d05
dc.identifier.otherRIS: urn:B310CEA4E7566BEC3D682C33410EA068
dc.identifier.otherRIS: 10.1103/PhysRevResearch.3.013090
dc.identifier.otherArXiv: http://arxiv.org/abs/2012.01545v1
dc.identifier.urihttps://hdl.handle.net/2164/15747
dc.descriptionACKNOWLEDGMENTS We would like to acknowledge support from the Vannevar Bush Faculty Fellowship program sponsored by the Basic Research Office of the Assistant Secretary of Defense for Research and Engineering and funded by the Office of Naval Research through Grant No. N00014-16-1-2828.en
dc.format.extent14
dc.language.isoeng
dc.relation.ispartofPhysical Review Researchen
dc.rightsPublished by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article’s title, journal citation, and DOI. https://creativecommons.org/licenses/by/4.0/en
dc.subjectcs.LGen
dc.subjectcs.AIen
dc.subjectmath.DSen
dc.subjectphysics.data-anen
dc.subjectQC Physicsen
dc.subjectQA Mathematicsen
dc.subject.lccQCen
dc.subject.lccQAen
dc.titleMachine learning prediction of critical transition and system collapseen
dc.typeJournal articleen
dc.contributor.institutionUniversity of Aberdeen.Mathematical Sciences (Research Theme)en
dc.contributor.institutionUniversity of Aberdeen.Environment and Food Securityen
dc.contributor.institutionUniversity of Aberdeen.Physicsen
dc.contributor.institutionUniversity of Aberdeen.Institute for Complex Systems and Mathematical Biology (ICSMB)en
dc.description.statusPeer revieweden
dc.description.versionPublisher PDFen
dc.identifier.doihttps://doi.org/10.1103/PhysRevResearch.3.013090
dc.identifier.urlhttp://arxiv.org/abs/2012.01545v1en


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