气候变化领域集成服务门户(CCPortal): Using machine learning to anticipate tipping points and extrapolate to post-tipping dynamics of non-stationary dynamical systems

CCPortal

DOI	10.1063/5.0131787
	Using machine learning to anticipate tipping points and extrapolate to post-tipping dynamics of non-stationary dynamical systems
	Patel, Dhruvit; Ott, Edward
发表日期	2023
ISSN	1054-1500
EISSN	1089-7682
卷号	33 期号:2
英文摘要	The ability of machine learning (ML) models to extrapolate to situations outside of the range spanned by their training data is crucial for predicting the long-term behavior of non-stationary dynamical systems (e.g., prediction of terrestrial climate change), since the future trajectories of such systems may (perhaps after crossing a tipping point) explore regions of state space which were not explored in past time-series measurements used as training data. We investigate the extent to which ML methods can yield useful results by extrapolation of such training data in the task of forecasting non-stationary dynamics, as well as conditions under which such methods fail. In general, we find that ML can be surprisingly effective even in situations that might appear to be extremely challenging, but do (as one would expect) fail when too much extrapolation is required. For the latter case, we show that good results can potentially be obtained by combining the ML approach with an available inaccurate conventional model based on scientific knowledge.
语种	英语
WOS研究方向	Mathematics, Applied ; Physics, Mathematical
WOS类目	Science Citation Index Expanded (SCI-EXPANDED)
WOS记录号	WOS:000940884700001
来源期刊	CHAOS
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/281420
作者单位	University System of Maryland; University of Maryland College Park
推荐引用方式 GB/T 7714	Patel, Dhruvit,Ott, Edward. Using machine learning to anticipate tipping points and extrapolate to post-tipping dynamics of non-stationary dynamical systems[J],2023,33(2).
APA	Patel, Dhruvit,&Ott, Edward.(2023).Using machine learning to anticipate tipping points and extrapolate to post-tipping dynamics of non-stationary dynamical systems.CHAOS,33(2).
MLA	Patel, Dhruvit,et al."Using machine learning to anticipate tipping points and extrapolate to post-tipping dynamics of non-stationary dynamical systems".CHAOS 33.2(2023).