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Benchmarks for identification of ordinary differential equations from time series data

By Peter Gennemark and Dag Wedelin

Abstract

Motivation: In recent years, the biological literature has seen a significant increase of reported methods for identifying both structure and parameters of ordinary differential equations (ODEs) from time series data. A natural way to evaluate the performance of such methods is to try them on a sufficient number of realistic test cases. However, weak practices in specifying identification problems and lack of commonly accepted benchmark problems makes it difficult to evaluate and compare different methods

Topics: Original Papers
Publisher: Oxford University Press
OAI identifier: oai:pubmedcentral.nih.gov:2654804
Provided by: PubMed Central

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