A finite element model in conjunction with stochastic number program that can automatically specify random damages of various extents is developed.
The noiseless sampling method is as follows: For formula (6), generate a stochastic number x 1 between [− 1,1] and a stochastic number x 2 between [− 10,10].
For formula (7), generate a stochastic number x 1 between [− 1.1832,1.1832], use the same approach to calculate x 3, and generate a stochastic number between [− 1,1] and evaluate it as x 2. The algorithm will finish until it gets enough amount of sampling.
First, mathematical models developed based on different characteristics: type of parameters (deterministic, probabilistic or stochastic), number and type of objective function, numbers of commodity and modes, relocation time, number of relocation and relocating facilities, time horizon, budget and capacity constraints and their applicability.
Denote stochastic reproduction number (mathscr{R} _{s}=mathscr{R}_{0}-frac{sigma_{2}^{2}}{2(mu +delta +gamma )}), we have proved that the (mathscr{R}_{s}) is a threshold of model (2) for the disease to die out or persist, and noise intensities can change the value of the stochastic reproduction number (mathscr{R} _{s}).
The stochastic large-number character of biological systems lies at the very heart of biological physics and is so dominant that the emergence of "new" laws of physics on higher levels of complexity was already claimed in the early 1940s [ 3].
It is generally assumed that the loss of a tumor suppressor gene or the gain of an Oncogene is the mechanism by which chromosomal alterations cause PNETs, but stochastic chromosomal number changes are also possible.
Moreover, each genotype, except DKO, possess two modes of responses; acute-stochastic (small number of immune-related genes) and collective modes (rest of ORFs).
At these count numbers, stochastic fluctuations may become important, and it has been argued that stochastic reaction-diffusion models are best suited to describe biological spatio-temporal systems [ 5].
In stochastic computation, real numbers are represented by random binary bit streams and information is carried in the statistics of the binary streams [ 40].
