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dc.contributor.authorSpendlove, Kelly T.
dc.contributor.authorBerwald, Jesse
dc.contributor.authorGedeon, Tomas
dc.identifier.citationK. Spendlove, J. Berwald and T. Gedeon, “Predicting High-Codimension Critical Transitions In Dynamical Systems Using Active Learning”, Mathematical and Computer Modelling of Dynamical Systems, 19(6), 557-574, (2013), DOI:10.1080/13873954.2013.801866.en_US
dc.description.abstractComplex dynamical systems, from those appearing in physiology and ecology to Earth system modelling, often experience critical transitions in their behaviour due to potentially minute changes in their parameters. While the focus of much recent work, predicting such bifurcations is still notoriously difficult. We propose an active learning approach to the classification of parameter space of dynamical systems for which the codimension of bifurcations is high. Using elementary notions regarding the dynamics, in combination with the nearest-neighbour algorithm and Conley index theory to classify the dynamics at a predefined scale, we are able to predict with high accuracy the boundaries between regions in parameter space that produce critical transitions.en_US
dc.titlePredicting High-Codimension Critical Transitions In Dynamical Systems Using Active Learningen_US
mus.citation.journaltitleMathematical and Computer Modelling of Dynamical Systemsen_US
mus.identifier.categoryPhysics & Mathematicsen_US
mus.relation.collegeCollege of Letters & Scienceen_US
mus.relation.departmentMathematical Sciences.en_US
mus.relation.universityMontana State University - Bozemanen_US
mus.contributor.orcidGedeon, Tomas|0000-0001-5555-6741en_US

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