Using machine learning to predict catastrophes in dynamical systems

DOI10.1016/j.cam.2011.11.006zbMath1237.65141OpenAlexW2145827601MaRDI QIDQ765272

Jesse Berwald, Tomáš Gedeon, John W. Sheppard

Publication date: 19 March 2012

Published in: Journal of Computational and Applied Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cam.2011.11.006

zbMATH Keywords

predictiondynamical systemsnumerical examplesConley indexfinancial marketsmachine learningNonlinear dynamical systemscomplex ecosystemsEarth's climatelocations of critical transitionsmachine learning method

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Ecology (92D40) Meteorology and atmospheric physics (86A10) Auctions, bargaining, bidding and selling, and other market models (91B26) Strange attractors, chaotic dynamics of systems with hyperbolic behavior (37D45) Numerical chaos (65P20) Prediction theory (aspects of stochastic processes) (60G25)

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