Sentence examples for mean field predictions from inspiring English sources

Properly taking fluctuations into account is shown to lead to higher sputtering at sub-threshold energies compared to mean field predictions.

This comparison shows that the mean field predictions are substantially superior to those of population balance as judged by the close proximity of results from the former to those from stochastic simulations.

One can see that the order parameter vanishes at and above the critical temperature (k_{B}T/NJ=1) and also the finite size numerical results approach to that of the mean field predictions reasonably well as the number of spins increases.

The black-short-dashed line is for (N=100), the blue-long-dashed line is for (N=500) and the red-solid line is the mean field prediction.

Therefore, in addition to mean-field predictions of transmitted resistance we also predicted the dynamics of the variance and skewness of these stochastic fluctuations by formulating and using a stochastic dynamic version of the deterministic model (see Mathematical Details S1 section 2.1).

'SF' means stochastic simulations and 'MM' means mean-field predictions.

From this angle, the stochastic simulations agree well with the mean-field predictions.

From Figure 2 we can see that the stochastic simulations are in accordance with mean-field predictions disregarding the slight fluctuations for the effect of the stochastic factor.

Especially, one can see that the larger transmission rates from infected vectors to susceptible individuals (gamma_{1}) or from infected individuals to susceptible vectors (gamma_{2}), the better the simulations accord with the mean-field predictions.

Considering the factor that the epidemic threshold (lambda_{c}) of stochastic simulations is larger than the one of the mean-field predictions, we think the stochastic simulations are reasonably consistent with the theoretic results.

To test this approximation we compared the mean-field predictions obtained by solving the Master equation to those obtained by the numerical integration of the deterministic version of the model for the duration of interest (i.e., up to 2009).