Sentence examples for using the stochastic sampling from inspiring English sources

In this framework, the nuclear data uncertainties related to cross-sections, neutron multiplicity and fission spectrum, provided via SCALE-6.2b4 based variance-covariance matrices, are propagated using the stochastic sampling method in all types of core calculations, including cycle depletion, validation against flux measurements and safety calculations typically required for reload licensing.

Selection of the individuals is developed using the stochastic universal sampling procedure together with an elitist selection scheme and the generation of the offspring population is put into effect using the classical binary multipoint crossover (performed at two points) and uniform mutation operators.

There are many papers on the persistence in mean and extinction for stochastic models, and a common means to do this is by using the stochastic comparison theorem and the sample Lyapunov exponent; see [7, 20].

Our method allows us to take advantage of the structure of HMMs to sample over all possible breakpoints using the stochastic Forwards-Backwards algorithm, assuming sufficient MCMC iterations.

The consequences for the minimal required sample sizes and their 95% confidence intervals of the different scenarios using the stochastic model are depicted in Figure 3.

For comparisons, we implement a brute force method [3] using 3000 samples to generate reference images and the time-dependent shadow mapping (TSM) using the stochastic rasterization [5].

A comparison of testing strategies using the stochastic model.

Input uncertainties are quantified and mapped to the stochastic space using the stochastic collocation technique.

The article also reviews the development of the qFSM methodology in the context of single-molecule imaging approaches that make use of the stochastic sampling paradigm to reconstruct the architecture of macromolecular assemblies with super-resolution.

This is essentially a high-dimensional version of the stochastic sampling used in Kriging [7].

We found the stochastic sampling algorithm accurately estimates the true coverage of the genomes (Table 1).