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The process model – identified based on a literature review and using new experimental data – accounts for factors influencing photoautotrophic and heterotrophic microalgal growth, nutrient uptake and storage (i.e. Droop model) and decay of microalgae.
The exclusion of the model involving cg13543854 and rs568727 due to a low frequency of selection among the 1,000 bootstrap samples indicates that this model, identified based on the original data, is likely to be a random finding.
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Lastly, the final model was identified based on model comparison.
The material parameters of the LYP steels for two analytical constitutive models (the Chaboche model and the Hu et al. model) were identified based on the experimental data.
We evaluated four different models: Linear: Exponential: Michaelis-Menton: Power: For each data set, the preferred model was identified based on Akaike's information criterion (AIC) (U.S. EPA 2000a, 2001).
The parameters (kernels) of the low-dimensional model are identified based on impulse functions, which offer a significant computational advantage over the full-order models, e.g., a computational fluid dynamics (CFD -based sCFD -based
A plant model is identified based on experimental data.
Time constants of the model are identified based on Pareto optimization.
Parameters of the biomechanical model are identified based on experimental kinematic data.
Some unknown parameters of the ICSTR model are identified based on experimental data collected from a zinc production factory in China.
The best ANN algorithm and model are identified based on minimum mean absolute error (MAE) and root mean square error (RMSE) and maximum linear correlation coefficient (R).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com