This paper presents a consistent and arbitrage-free multifactor model of the term structure of interest rates in which yields at selected fixed maturities follow a parametric multivariate Markov diffusion process with " stochastic volatility. " The yield of any zero-coupon bond is taken to be a maturity-dependent affine combination of the selected " basis " set of yields. We provide necessary a...

Due to the probabilistic nature and uncertainties of structural parameters, reliability-based optimization will enable engineers to account for the safety of the structures and allow for its decision making applicability. Thus, reliability-based design will substitute deterministic rules of codes of practice. Space structures are of those types that have an exceedingly high range of applicabili...

A stochastic model for generating disturbances in landscapes that interfaces with geographic information systems (GIS) is presented. The model operates on a lattice (rectangular array of points) using a space–time Markov process, which gives a stochastic simulation of growth patterns in terms of parameters of the local region. The model generates disturbance patterns on the landscape based on u...

In this paper, we describe a decompositional approach to convergence proofs for stochastic hybrid systems given as probabilistic hybrid automata. We focus on a concept called “stability in probability,” which implies convergence of almost all trajectories of the stochastic hybrid system to a designated equilibrium point. By adapting classical Lyapunov function results to the stochastic hybrid c...

in this paper, a high-order and conditionally stable stochastic difference scheme is proposed for the numerical solution of $rm ithat{o}$ stochastic advection diffusion equation with one dimensional white noise process. we applied a finite difference approximation of fourth-order for discretizing space spatial derivative of this equation. the main properties of deterministic difference schemes,...

in this paper, a stochastic two-stage model is offered for optimization of the day-ahead scheduling of the microgrid. system uncertainties including dispatchable distributed generation and energy storage contingencies are considered in the stochastic model. for handling uncertainties, monte carlo simulation is employed for generation several scenarios and then a reduction method is used to d...