Marine Ecosystem Model Calibration through Enhanced Surrogate-Based Optimization.

Prieß, Malte, Koziel, Slawomir and Slawig, Thomas (2013) Marine Ecosystem Model Calibration through Enhanced Surrogate-Based Optimization. In: Simulation and Modeling Methodologies, Technologies and Applications. , ed. by Pina, N., Kacprzyk, J. and Filipe, J.. Advances in Intelligent Systems and Computing, 197 (2). Springer, Berlin, Germany, pp. 193-208. ISBN 978-3-642-34335-3 DOI 10.1007/978-3-642-34336-0_13.

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Supplementary data:


Mathematical optimization of models based on simulations usually requires a substantial number of computationally expensive model evaluations and it is therefore often impractical. An improved surrogate-based optimization methodology, which addresses these issues, is developed for the optimization of a representative of the class of one-dimensional marine ecosystem models. Our technique is based upon a multiplicative response correction technique to create a computationally cheap but yet reasonably accurate surrogate from a temporarily coarser discretized physics-based coarse model. The original version of this methodology was capable of yielding about 84% computational cost savings when compared to the fine ecosystem model optimization. Here, we demonstrate that by employing relatively simple modifications, the surrogate model accuracy and the efficiency of the optimization process can be further improved. More specifically, for the considered test case, the optimization cost is reduced three times, i.e., from about 15% to only 5% of the cost of the direct fine model optimization.

Document Type: Book chapter
Keywords: Marine Ecosystem Models; Surrogate-based Optimization; Parameter Optimization; Response Correction Data Assimilation
Research affiliation: OceanRep > The Future Ocean - Cluster of Excellence > FO-R11
Kiel University
OceanRep > GEOMAR > FB2 Marine Biogeochemistry > FB2-BM Biogeochemical Modeling
Kiel University > Kiel Marine Science
OceanRep > The Future Ocean - Cluster of Excellence
Refereed: Yes
Open Access Journal?: No
DOI etc.: 10.1007/978-3-642-34336-0_13
ISSN: 2194-5357
Projects: Future Ocean
Date Deposited: 11 Dec 2012 13:40
Last Modified: 23 Sep 2019 21:05

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