The influence of parameter fitting methods on model structure selection in automated modeling of aquatic ecosystems

Darko Čerepnalkoski, Katerina Taškova, Ljupčo Todorovski, Nataša Atanasova and Sašo Džeroski

Ecological Modelling, 2012, vol. 245, issue C, 136-165

Abstract: Modeling dynamical systems involves two subtasks: structure identification and parameter estimation. ProBMoT is a tool for automated modeling of dynamical systems that addresses both tasks simultaneously. It takes into account domain knowledge formalized as templates for components of the process-based models: entities and processes. Taking a conceptual model of the system, the library of domain knowledge, and measurements of a particular dynamical system, it identifies both the structure and numerical parameters of the appropriate process-based model. ProBMoT has two main components corresponding to the two subtasks of modeling. The first component is concerned with generating candidate model structures that adhere to the conceptual model specified as input. The second subsystem uses the measured data to find suitable values for the constant parameters of a given model by using parameter estimation methods. ProBMoT uses model error to rank model structures and select the one that fits measured data best.

Keywords: Aquatic ecosystems; Dynamical systems; Equation discovery; Process-based modeling; Parameter estimation; Meta-heuristic optimization (search for similar items in EconPapers)
Date: 2012
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:245:y:2012:i:c:p:136-165

DOI: 10.1016/j.ecolmodel.2012.06.001

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