Sentence examples for more realistic distribution from inspiring English sources

Model results for uniformly distributed season length indicate that with more realistic distribution functions and observed variability of season length graded control is rather improbable.

Figure 1 shows how the weighting by land-use provides a much more realistic distribution of employment.

In order to identify the effect of elevation on the correlation function, more realistic distribution functions need to be used.

For this reason, we employed a data-driven approach accounting for intrinsic correlations in human mobility and leading to a more realistic distribution of origin-destination pairs.

As an addition to the significant work of [12], in this work, we show exactly how elevation affects correlation if a more realistic distribution of scatterers (i.e., vMF) is to be used.

The improvement is attributed to the application of more realistic distribution functions to the aerosol size spectra rather than the new inclusion of dust and black carbonaceous aerosol into the categories.

In contrast to similar approaches [2], [3] forecast errors of wind and photovoltaic power are not modeled as normal distributions, which does not reflect reality [4], [5], [6], but by kernel density estimation to get more realistic distributions.

At systematically increased levels of data aggregation, the model was tested on two landscapes, one based on species patterns that were initially random and one based on more realistic distributions, over 500-year time periods for a southern California (Mediterranean-climate) landscape.

This study shows that the effect of assuming exponential distribution for infection periods instead of more realistic distributions varies with respect to the output of interest and to other factors.

We have shown that the effect of assuming exponential distribution for infection periods instead of more realistic distributions varies with respect to the output of interest and to other exogenous factors.

We then extend this model to additionally incorporate more realistic distributions for the infectious period; this is achieved by using the classical approach of breaking the infectious class into a number of new classes while preserving the total average time in these new classes (see, for example, [39] and [40]).