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As a result, when compared to a traditional AAM approach, segmentation is performed faster and model convergence is improved, attaining good results using small training sets.
Model convergence is tested with a mesh sensitivity study, and the model's ability in evaluating practical design changes in the CP system is demonstrated.
This paper is completed with dynamic simulations where, the model convergence is studied, the contribution of the different heat transfer processes is analyzed, and the impact of the environment conditions to thermal losses is evaluated.
Data plugged in model specification within tailored computing environments allow research to keep track of computational efforts: such as log-likelihood values generated for each observation until model convergence is achieved.
In the model, convergence is rather fast (basically it is of the order of magnitude of the inverse of the turnover rates), so the equilibrium in which the system falls gives a good idea of how the system behaves in the few weeks that follow the perturbation.
Model convergence is checked by Brooks, Gelman, Rubin diagnostics plots [ 26], autocorrelations, density and history plots.
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However, model convergence was generally not achieved when fitting c.
Our Bayesian meta-analyses had GOF scores between 0.46 and 0.50 for all fish metrics, confirming good model fits for estimating effect-size relationships, and model convergence was deemed adequate in every instance [51].
Unfortunately, model convergence was never achieved once pathways were included between GAD and MDD symptoms.
Model convergence was monitored using a Monte Carlo SE threshold of 0.1.
Model convergence was assessed according to Gelman and Rubin's convergence diagnostic, the potential scale reduction factor [ 24].
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