Illustrative examples demonstrate modeling reliability, as well as enhanced modeling and analysis productivity, compared to the manual process.
Evolving nuclear energy programs expect to use enhanced modeling and simulation (M&S) capabilities, using multiscale, multiphysics modeling approaches, to reduce both cost and time from the design through the licensing phases.
The main objective of this study is thus to contribute to the debate over nuclear energy and the environment with an enhanced model and variables.
From these tables we can estimate the comparative average weighted accuracies of the different predictive models constructed on the 17 genes of the enhanced model, and on the 70 and 231 genes selected by van't Veer and coworkers [ 3].
Additionally, an analytical solution is provided for a propagating interface (macroscopic transformation front) both for the gradient-enhanced model and for its micromorphic version.
The nonlinearity of the biotechnological processes and the absence of cheap and reliable instrumentation require an enhanced modelling effort and estimation strategies for the state and the kinetic parameters.
However, the specific characteristics of these processes, such as complexity, nonlinearity, and absence of cheap and reliable instrumentation, require an enhanced modelling effort and advanced kinetic parameter estimation strategies.
In models for intracranial injury and aspiration pneumonia, the c-statistics of the original and enhanced models were equal.
Comparing the predictive power of the original Charlson model and the enhanced models using c-statistics, the enhanced models were slightly superior to the original in all but three MRDx categories (See Additional file 1: Tables S5-S28 to review the model coefficients).
The nonlinearity of these processes and the absence of suitable instrumentation require an enhanced modelling effort and modern kinetic parameter estimation strategies.
