The RRVE proposed here exhibits random elastic properties, which are assigned based on stochastic distributions.
Geostatistical approaches based on stochastic simulations provide the spatial distribution of SHP and the uncertainty attached to their estimates.
The model was constructed based on stochastic demand and used products with known distribution.
Exact characterization of probability landscape is useful, as most network studies are based on stochastic simulation, and relative little is known at the level of the full stochastic landscape probability distribution, even for simple toy systems.
By contrast, the integration of sensory and internal distributions in our model reduced the variability of simulated time estimates based on stochastic stimuli.
NORMA is based on stochastic gradient descent.
Reliability analysis is based on stochastic discrete event models like stochastic Petri nets.
In this paper, the cognitive femtocell network topology is based on stochastic geometry; macrocell and femtocell base stations are modeled as two independent Voronoi tessellations, where MBSs and FBSs follow Poisson point process (PPP) distribution in their own tessellation.
Our mechanism is based on stochastic datagram relocation.
The algorithm is developed based on stochastic finite-element method.
