Meta-Model Framework for Surrogate-Based Parameter Estimation in Dynamical Systems
Meta-Model Framework for Surrogate-Based Parameter Estimation in Dynamical Systems
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Ithaca: Cornell University Library, arXiv.org
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English
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Ithaca: Cornell University Library, arXiv.org
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Contents
The central task in modeling complex dynamical systems is parameter estimation. This task involves numerous evaluations of a computationally expensive objective function. Surrogate-based optimization introduces a computationally efficient predictive model that approximates the value of the objective function. The standard approach involves learning...
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Full title
Meta-Model Framework for Surrogate-Based Parameter Estimation in Dynamical Systems
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TN_cdi_proquest_journals_2245978491
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2245978491
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E-ISSN
2331-8422
DOI
10.48550/arxiv.1906.09088
