Machine learning prediction of critical transition and system collapse

Kong, Ling-WeiFan, Hua-WeiGrebogi, CelsoLai, Ying-Cheng2021-01-292021-01-292021-01-28Kong, 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.3.0130902643-1564RIS: urn:B310CEA4E7566BEC3D682C33410EA068RIS: 10.1103/PhysRevResearch.3.013090ArXiv: http://arxiv.org/abs/2012.01545v1ORCID: /0000-0002-9811-4617/work/107062302https://hdl.handle.net/2164/15747ACKNOWLEDGMENTS 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. N00014-16-1-2828.142601846engSubstantive connection via an eligible employment contractcs.LGcs.AImath.DSphysics.data-anQC PhysicsQA MathematicsQCQAMachine learning prediction of critical transition and system collapseJournal article10.1103/PhysRevResearch.3.013090http://arxiv.org/abs/2012.01545v131