Ayala Solares, J.R. and Wei, H.-L. orcid.org/0000-0002-4704-7346 (2015) Nonlinear model structure detection and parameter estimation using a novel bagging method based on distance correlation metric. Nonlinear Dynamics. ISSN 0924-090X
Abstract
System identification has been applied in diverse areas over past decades. In particular, parametric modelling approaches such as linear and nonlinear autoregressive with exogenous inputs models have been extensively used due to the transparency of the model structure. Model structure detection aims to identify parsimonious models by ranking a set of candidate model terms using some dependency metrics, which evaluate how the inclusion of an individual candidate model term affects the prediction of the desired output signal. The commonly used dependency metrics such as correlation function and mutual information may not work well in some cases, and therefore, there are always uncertainties in model parameter estimates. Thus, there is a need to introduce a new model structure detection scheme to deal with uncertainties in parameter estimation. In this work, a distance correlation metric is implemented and incorporated with a bagging method. The combination of these two implementations enhances the performance of existing forward selection approaches in that it provides the interpretability of nonlinear dependency and an insightful uncertainty analysis for model parameter estimates. The new scheme is referred as bagging forward orthogonal regression using distance correlation (BFOR-dCor) algorithm. A comparison of the performance of the new BFOR-dCor algorithm with benchmark algorithms using metrics like error reduction ratio, mutual information, or the Reversible Jump Markov Chain Monte Carlo method has been carried out in dealing with several numerical case studies. For ease of analysis, the discussion is restricted to polynomial models that can be expressed in a linear-in-the-parameters form.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © European Union 2015. |
Keywords: | Nonlinear system identification; NARX models; Bootstrap method; Bagging method; Distance correlation |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield) |
Funding Information: | Funder Grant number ENGINEERING AND PHYSICAL SCIENCE RESEARCH COUNCIL EP/H00453X/1 ENGINEERING AND PHYSICAL SCIENCE RESEARCH COUNCIL EP/I011056/1 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 05 Apr 2023 15:31 |
Last Modified: | 05 Apr 2023 15:31 |
Status: | Published |
Publisher: | Springer |
Refereed: | Yes |
Identification Number: | 10.1007/s11071-015-2149-3 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:197866 |