In order to catch up with reality, all the macro-decisions related to long-term mining production planning must be made simultaneously and under uncertain conditions of determinant parameters. By taking advantage of the chance-constrained programming, this paper presents a stochastic model to create an optimal strategy for producing bimetallic deposit open-pit mines under certain and uncertain ...

in this paper, we introduce an efficient method based on haar wavelet to approximate a solutionfor the two-dimensional linear stochastic fredholm integral equation. we also give an example to demonstrate the accuracy of the method.

We give a review of the relativistic stochastic process denominated with the acronym ROUP, standing for relativistic Ornstein-Ohlenbeck process. This stochastic process was introduced in 1997 by Debbasch, Mallick and Rivet [J. Stat. Phys. 88:945 966 ] as a simpli ed model of irreversibility in a relativistic framework. This allows an investigation of the paradox arising when examining the large...

In this tutorial we give an introduction to stochastic process algebras and their use in performance modelling, with a focus on the PEPA formalism. A brief introduction is given to the motivations for extending classical process algebra with stochastic times and probabilistic choice. We then present an introduction to the modelling capabilities of the formalism and the tools available to suppor...

1.1 Probability Triple We introduce the probability triple (Ω,F , P ), which is the foundation of the probability analysis. Let Ω be a set and F be a collection of subsets of Ω. A point ω ∈ Ω ia a sample and A ∈ F is an event. The probability measure P assigns 0 ≤ P (A) ≤ 1 for each event A ∈ F , i.e. the probability of event A occurs: Definition The triple (Ω,F , P ) is the probability triple ...

Stochastic partition models tailor a product space into a number of rectangular regions such that the data within each region exhibit certain types of homogeneity. Due to constraints of partition strategy, existing models may cause unnecessary dissections in sparse regions when fitting data in dense regions. To alleviate this limitation, we propose a parsimonious partition model, named Stochast...

in the present article, we focus on the numerical approximation of stochastic partial differential equations of itˆo type with space-time white noise process, in particular, parabolic equations. for each case of additive andmultiplicative noise, the numerical solution of stochastic diffusion equations is approximated using two stochastic finite difference schemes and the stability and consisten...