Sentence examples for models to complex from inspiring English sources

Based on our review, models used for forward (biomarker) and reverse (exposure) predictions varied tremendously in terms of their complexity, ranging from simple analytical models to complex physiologically based pharmacokinetic (PBPK) models involving Markov Chain Monte Carlo analyses (Allen et al. 2007; Lyons et al. 2008).

The Model Builder provides a visual modeling tool for designing arbitrary compartmental models, ranging from simple SIR models to complex compartmentalization in which multiple interventions can be considered along with disease-associated complications and other effects.

This study encourages the further application of cellular automata based models to complex problems.

Resolving all the scales of a turbulent flow is too costly, while employing highly empirical turbulence models to complex problems could give inaccurate simulation results.

There are many possible reasons for this, including difficulty in translating tightly structured animal stroke models to complex human clinical scenarios and inadequate penetration of neuroprotective agents into the poorly perfused hemisphere andischemic penumbra.

aDREAM refers to non‐textual formal descriptions of agent‐based models such as those obtained by converting agent‐based models to complex networks and subsequently applying quantitative centrality measures.bhttp://publicationethics.org/resources/guidelinescFor reference, kindly review http://publicationethics.org/files/u2/2003pdf12.pdf.org/files/u2/2003pdf12.pdf

We propose and compare six different ways of mapping the modified q-voter model to complex networks.

In practice, and partly due to limitations of the manual approach, application of forward modeling to complex situations involving arbitrary distributions of stations has been difficult.

A good deal of criticism has been aimed at TTM, regarding, for example, the difficulty of applying the model to complex dietary behavior [ 3, 6– 11].

There are several widely accepted methods for modelling metabolism, ranging from highly detailed kinetic models to less complex stoichiometric models.

The basic strategy was moving from simple models to more complex models and from a few variables to more.