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This SFR model is a simplified equivalent model, and its modeling procedure is based on the generator parameters.
Comparing obtained results from developed modeling with available experimental data, the developed modeling procedure is validated.
An optical modeling procedure is developed to predict and model the colour of electro-coloured anodized aluminium that has been modified in pore structure for the generation of interference colours.
A multiscale modeling procedure is introduced in this paper for modeling continuous high-shear wet granulation.
Different model order selection criteria are comparatively discussed, and the modeling procedure is considered to improve the calculation efficiency.
Whichever modeling procedure is used -- whether robust Poisson or Cox, or log-binomial models --, the Prarelyly accomplishes its purpose in providing a meaningful estimate within the potential outcomes model framework.
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The modeling procedure was benchmarked by comparing models of an existing facility against measurements.
In this method, Bayesian information criterion and the ARMA(2n,2n – 1) modeling procedure are first used to automatically select the optimal model order, and the auto regressive moving averaging models are built based on ambient data, then the low-frequency oscillation modal frequency and damping ratio are identified.
The modeling procedure was developed based on the five Organization for Economic Cooperation and Development OECDD) principles for QSAR models.
The results produced by the predictive modeling procedure are optimally predicted values for the responses and for all model parameters, with reduced predicted uncertainties that are smaller than either the measured or the computed uncertainties.
Next, the general techniques of optimization that allow automation of the modeling procedure are described.
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