Optimization of model parameters and experimental designs with the Optimal Experimental Design Toolbox (v1.0) exemplified by sedimentation in salt marshes
The geosciences are a highly suitable field of application for optimizing model parameters and experimental designs especially because many data are collected. <br><br> In this paper, the weighted least squares estimator for optimizing model parameters is presented together with its asym...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2015-03-01
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| Series: | Geoscientific Model Development |
| Online Access: | http://www.geosci-model-dev.net/8/791/2015/gmd-8-791-2015.pdf |
| _version_ | 1819059466978459648 |
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| author | J. Reimer M. Schuerch T. Slawig |
| author_facet | J. Reimer M. Schuerch T. Slawig |
| author_sort | J. Reimer |
| collection | DOAJ |
| description | The geosciences are a highly suitable field of application for optimizing model
parameters and experimental designs especially because many data are
collected.
<br><br>
In this paper, the weighted least squares estimator for optimizing model
parameters is presented together with its asymptotic properties. A popular
approach to optimize experimental designs called local optimal experimental
designs is described together with a lesser known approach which takes into
account the potential nonlinearity of the model parameters. These two
approaches have been combined with two methods to solve their underlying
discrete optimization problem.
<br><br>
All presented methods were implemented in an open-source MATLAB toolbox
called the <i>Optimal Experimental Design Toolbox</i> whose structure and
application is described.
<br><br>
In numerical experiments, the model parameters and experimental design were
optimized using this toolbox. Two existing models for sediment concentration
in seawater and sediment accretion on salt marshes of different complexity
served as an application example. The advantages and disadvantages of these
approaches were compared based on these models.
<br><br>
Thanks to optimized experimental designs, the parameters of these models
could be determined very accurately with significantly fewer measurements
compared to unoptimized experimental designs. The chosen optimization
approach played a minor role for the accuracy; therefore, the approach with the
least computational effort is recommended. |
| first_indexed | 2024-12-21T14:11:33Z |
| format | Article |
| id | doaj.art-a07c622489e34e9c9468190d48b6a062 |
| institution | Directory Open Access Journal |
| issn | 1991-959X 1991-9603 |
| language | English |
| last_indexed | 2024-12-21T14:11:33Z |
| publishDate | 2015-03-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Geoscientific Model Development |
| spelling | doaj.art-a07c622489e34e9c9468190d48b6a0622022-12-21T19:01:01ZengCopernicus PublicationsGeoscientific Model Development1991-959X1991-96032015-03-018379180410.5194/gmd-8-791-2015Optimization of model parameters and experimental designs with the Optimal Experimental Design Toolbox (v1.0) exemplified by sedimentation in salt marshesJ. Reimer0M. Schuerch1T. Slawig2Institute of Computer Science, Future Ocean – Kiel Marine Sciences, Christian-Albrechts-University Kiel, 24098 Kiel, GermanyInstitute of Geography, Future Ocean – Kiel Marine Sciences, Christian-Albrechts-University Kiel, 24098 Kiel, GermanyInstitute of Computer Science, Future Ocean – Kiel Marine Sciences, Christian-Albrechts-University Kiel, 24098 Kiel, GermanyThe geosciences are a highly suitable field of application for optimizing model parameters and experimental designs especially because many data are collected. <br><br> In this paper, the weighted least squares estimator for optimizing model parameters is presented together with its asymptotic properties. A popular approach to optimize experimental designs called local optimal experimental designs is described together with a lesser known approach which takes into account the potential nonlinearity of the model parameters. These two approaches have been combined with two methods to solve their underlying discrete optimization problem. <br><br> All presented methods were implemented in an open-source MATLAB toolbox called the <i>Optimal Experimental Design Toolbox</i> whose structure and application is described. <br><br> In numerical experiments, the model parameters and experimental design were optimized using this toolbox. Two existing models for sediment concentration in seawater and sediment accretion on salt marshes of different complexity served as an application example. The advantages and disadvantages of these approaches were compared based on these models. <br><br> Thanks to optimized experimental designs, the parameters of these models could be determined very accurately with significantly fewer measurements compared to unoptimized experimental designs. The chosen optimization approach played a minor role for the accuracy; therefore, the approach with the least computational effort is recommended.http://www.geosci-model-dev.net/8/791/2015/gmd-8-791-2015.pdf |
| spellingShingle | J. Reimer M. Schuerch T. Slawig Optimization of model parameters and experimental designs with the Optimal Experimental Design Toolbox (v1.0) exemplified by sedimentation in salt marshes Geoscientific Model Development |
| title | Optimization of model parameters and experimental designs with the Optimal Experimental Design Toolbox (v1.0) exemplified by sedimentation in salt marshes |
| title_full | Optimization of model parameters and experimental designs with the Optimal Experimental Design Toolbox (v1.0) exemplified by sedimentation in salt marshes |
| title_fullStr | Optimization of model parameters and experimental designs with the Optimal Experimental Design Toolbox (v1.0) exemplified by sedimentation in salt marshes |
| title_full_unstemmed | Optimization of model parameters and experimental designs with the Optimal Experimental Design Toolbox (v1.0) exemplified by sedimentation in salt marshes |
| title_short | Optimization of model parameters and experimental designs with the Optimal Experimental Design Toolbox (v1.0) exemplified by sedimentation in salt marshes |
| title_sort | optimization of model parameters and experimental designs with the optimal experimental design toolbox v1 0 exemplified by sedimentation in salt marshes |
| url | http://www.geosci-model-dev.net/8/791/2015/gmd-8-791-2015.pdf |
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