In the stochastic time-dependent variant, the travel time between two locations is a stochastic function that depends on the departure time at the first location.
The first part explains the mean behavior of the function we interpolate and the second part is a stochastic function with known mean and variance.
The strength and reliability of the beam, being a stochastic function of local stresses, is therefore morphology dependent, in addition to (coupled with) the classical inherent probabilistic nature, associated with surface defects and irregularities.
Molecular dynamics simulations show that time to failure is a stochastic function of applied shear stress, and that for a given loading time behavior is elastic for sufficiently small shear loads.
Furthermore, in most of the literature, the JR-NMM includes a term representing extrinsic input or background noise, which essentially is done by declaring that input function to be a stochastic process.
In the present model, the escape of self-reactive naïve T-cells from deletion in the thymus and self-reactive resting T-cells which are capable to be activated under specific environmental triggers, such as infections, were modelled using a stochastic function by uniformly distributed production of resting Teff and Treg cells over time.
They are used to identify a stochastic function and a set of random numbers.
Formally, (84) implies that s(h,Λ) is a stochastic subgradient of the dual function.
Particle swarm optimization (PSO) is a stochastic optimization method for nonlinear functions based on the reproduction of social behavior developed by Berhart and Kennedy [5, 6] in 1995.
DE is a stochastic population-based optimization algorithm with real parameters and real-valued functions.
