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Table 6 lists the range of parameter values applied in this study.
To this end, a systematic approach was adopted in which dissolution rates for individual minerals were calibrated to the results of the single mineral columns and the resulting parameter values applied to the more complex columns.
Parameter values applied were h = 2 with 4 or 8 weeks of baseline (BL) data and 3 ≤ k ≤ 6.
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Table 3 Key GA behavioral parameters values applied to four runs and the optimal objective function value found after 2000 iterations Run 1 Run 2 Run 3 Run 4 P m 0.8 0.5 0.2 Variable P c 0.2 0.5 0.8 Optimal solution found TMD (m) 2352 2352 2354 2352 The optimal objective function value for each iteration of each run is illustrated as trends in Fig. 6 (Case 1).
Given that some parameters are known or highly constrained, one may obtain the best model fit to the data for a particular subset of model parameters, and one may also, for some but not all of the optimizers, constrain the range for each parameter value, applying scientific judgment.
An activity-based costing algorithm was developed to which parameter values were applied.
These parameter values were applied to all the data of the same type.
The process of characterizing parameter values is applied to each model structure and the resulting ensemble is the collection of model structures and their associated probabilistic parameter distributions.
To address the uncertainty in the cost per case estimates and other parameter values, we applied a range of values as indicated in Table 1.
ML analysis was performed using the GTR+I+G model [ 41], and optimized parameter values were applied after the determination using Modeltest.
Base case values were modified for the following parameters: Transition probabilities: The same values applied for methadone were also assumed for B/N combination.
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CEO of Professional Science Editing for Scientists @ prosciediting.com