Numerical continuation in nonlinear experiments using local Gaussian process regression

DOI10.1007/s11071-019-05118-yzbMath1430.74063arXiv1901.06970OpenAlexW2968473228MaRDI QIDQ2296654

Jan Sieber, A. D. Shaw, L. Renson, David A. W. Barton, Simon A. Neild

Publication date: 18 February 2020

Published in: Nonlinear Dynamics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1901.06970

zbMATH Keywords

active data selectionGaussian process regressioncontrol-based continuationnonlinear experimentregression-based continuation

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) General nonlinear regression (62J02) Random vibrations in dynamical problems in solid mechanics (74H50)

Related Items (2)

Methods of continuation and their implementation in the COCO software platform with application to delay differential equations ⋮ Data-driven control of agent-based models: an equation/variable-free machine learning approach

Uses Software

• GitHub
• rtc

Cites Work

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• A SURVEY OF METHODS FOR COMPUTING (UN)STABLE MANIFOLDS OF VECTOR FIELDS
• Elements of applied bifurcation theory

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