It is shown that a digital simulation of a noise induced phase transition using an algorithm consistent with the Ito stochastic calculus is in agreement with the predictions of that theory, whereas experiments with an analogue simulator yield measured results in agreement with the predictions of the Stratonovich theory.

In this paper, we consider a stochastic Gilpin-Ayala model under regime switching. Obtain the optimal harvesting effort and the maximum sustained yield by investigating the condition of average boundness of the system, and the ergodicity of the Markov chain. Also, through an example, we have proved our conclusion.

Stochastic processes underlie all of biology, from the large-scale processes of evolution to the fine-scale processes of biochemical interactions. Consequently, the analysis of biological data frequently necessitates the use of Markov models. While these models sometimes yield analytic solutions, simulations can provide intuition when analytic results are intractable. This vignette presents a f...

Most epidemic spreading models assume memoryless systems and statistically independent infections. Nevertheless, many real-life cases are manifestly time-sensitive and may be strongly correlated. We study the effect of non-Markovian stochastic dynamics on the SIS model, in random and scale-free networks, and propose a novel microscopic description to account for cooperation. Initial exploratory...

We discuss the use of stochastic collocation for the solution of optimal control problems which are constrained by stochastic partial differential equations (SPDE). Thereby the constraining SPDE depends on data which is not deterministic but random. Assuming a deterministic control, randomness within the states of the input data will propagate to the states of the system. For the solution of SP...

We propose a model for the aggregate stock market together with its dividend yield and earnings yield so that the ex-ante risk premium could be extracted in an unobserved component modelling framework. We posit the model as a linked stochastic differential equation system and the linking variable is the ex-ante risk premium. By hypothesising a realistic dynamic structure for the ex-ante risk pr...

Optimization is a crucial step in the analysis of experimental results. Deterministic methods only converge on local optimums and require exponentially more time as dimensionality increases. Stochastic algorithms are capable of efficiently searching the domain space; however convergence is not guaranteed. This article demonstrates the novelty of the hybrid genetic algorithm (HGA), which combine...

in this paper, we present an application of the stochastic calculusto the problem of modeling electrical networks. the filtering problem have animportant role in the theory of stochastic differential equations(sdes). in thisarticle, we present an application of the continuous kalman-bucy filter for a rlcircuit. the deterministic model of the circuit is replaced by a stochastic model byadding a ...

performance evaluation of electricity distribution units is an important issue between researchers and regulators. classic data envelopment analysis models with deterministic data have been used by many authors to measure efficiency of power distribution units in different countries. however, data envelopment analysis with stochastic data are rarely used to measure efficiency of distribution co...