Using machine learning to predict catastrophes in dynamical systems
type: Item
instance of: scholarly article
title: Using machine learning to predict catastrophes in dynamical systems
zbMATH Open document ID: 1237.65141
author: Jesse Berwald
author: Tomáš Gedeon
author: John W. Sheppard
published in: Journal of Computational and Applied Mathematics
publication date: 2012-03-19T00:00:00Z
Mathematics Subject Classification ID: 65P20
Mathematics Subject Classification ID: 62M20
Mathematics Subject Classification ID: 60G25
Mathematics Subject Classification ID: 92D40
Mathematics Subject Classification ID: 91B26
Mathematics Subject Classification ID: 86A10
Mathematics Subject Classification ID: 37D45
zbMATH DE Number: 6015740
zbMATH Keywords: Conley index
zbMATH Keywords: dynamical systems
zbMATH Keywords: machine learning
zbMATH Keywords: prediction
zbMATH Keywords: numerical examples
zbMATH Keywords: Nonlinear dynamical systems
zbMATH Keywords: Earth's climate
zbMATH Keywords: financial markets
zbMATH Keywords: complex ecosystems
zbMATH Keywords: machine learning method
zbMATH Keywords: locations of critical transitions
MaRDI profile type: Publication
full work available at URL: j.cam.2011.11.006
OpenAlex ID: W2145827601
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DOI: 10.1016/J.CAM.2011.11.006
description: scientific article; zbMATH DE number 6015740