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After selection of an appropriate process model structure, parameter estimates have to be obtained based on real-life experiments.
After selecting an appropriate process model structure, parameter estimates have to be obtained based on real-life experiments.
The divergence between prior and posterior probability distributions at the model components is used as an indication on the inconsistency between model structure, parameter values, and other information used.
The model development may start with considering the network structure with kinetic rate expressions, model structure, parameter identification, and model validation, which may differ depending on the purpose of using a model [12].
The current model represents a significant refinement of our earlier version in terms of model structure, parameter assignment and scenario design [4].
For each candidate model structure, parameter estimation is performed to obtain a set of point estimates of the unknown model parameters that most adequately explains the observed system behavior.
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Distinction is made here between the context, model structure, parameters and input data.
The sensitivity of monitoring design to a number of model and design parameters is investigated, while model structure and parameter uncertainties are incorporated through user-specified scenarios.
both model structure and parameter errors.
Hydrological models are subject to significant sources of uncertainty including input data, model structure and parameter uncertainty.
The strategy consists of carefully designed identification experiments involving preliminary process tests and a final test, followed by judicious model structure selection, parameter estimation and model validation.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com