Cahn–Morral systems serve as models for several phase separation phenomena in multicomponent alloys. In this paper we study the dynamical aspects of nucleation in a stochastic version of these models using numerical simulations, concentrating on ternary, i.e., three-component, alloys on twodimensional square domains. We perform numerical studies and give a statistical classification for the dis...

An efficient method for finding a better maximizer of computationally extensive probability distributions is proposed on the basis of a Bayesian optimization technique. A key idea of the proposed method is to use extreme values of acquisition functions by Gaussian processes for the next training phase, which should be located near a local maximum or a global maximum of the probability distribut...

Wind energy as one of the most promising alternatives brings a set serious challenges in operation power systems because uncertain nature wind speed. To address this problem, it is essential to establish framework forecast comprehensive form information about end, an ensemble residual regression deep network designed understand fully time-variant and spatial features from historical data includ...

A modified Student’s t distribution is suggested for small scale fading statistics in line of sight and non line of sight conditions where the number of scatterers is small, and the central limit theorem does not hold. The new model is superior to the previously suggested POCA distribution, and has the natural characteristic of radial symmetry. The new model was tested against channel response ...

the rock masses in a construction site of underground cavern are generally not continuous, due to the presence of discontinuities, such as bedding, joints, faults, and fractures. the performance of an underground cavern is principally ruled by the mechanical behaviors of the discontinuities in the vicinity of the cavern. during underground excavation, many surrounding rock failures have close r...

This report introduces Bayesian logic networks (BLNs), a statistical relational knowledge representation formalism that is geared towards practical applicability. A BLN is a meta-model for the construction of a probability distribution from local probability distribution fragments (as in a Bayesian network) and global logical constraints formulated in first-order logic. An instance is thus a mi...

We consider the nonparametric density estimation problem for a quantity of interest computed from solutions of an elliptic partial differential equation with randomly perturbed coefficients and data. Our particular interest are problems for which limited knowledge of the random perturbations are known. We derive an efficient method for computing samples and generating an approximate probability...