Stochastic activity networks (SANs) are a powerful and flexible extension of Petri nets. However, SANs facilities are not enough for modeling and analysis of complex and large-scale systems. In order to provide such high-level modeling facilities, we have defined some new extensions for SANs. We intend to preserve all capabilities of SANs for performance, dependability and performability evalua...

In this paper, we propose a novel modeling method, Stochastic Game Nets(SGN). SGN is an good method to model and deal with the game issues, which takes advantages of both stochastic game theory and Stochastic Petri Nets. The SGN could inherit the efficient and flexible modeling approach of Stochastic Petri Nets, and also make well use of the game-theoretical framework from game theory. Meanwhil...

There has been a recent burst of activity in the atmosphere/ocean sciences community in utilizing stable linear Langevin stochastic models for the unresolved degree of freedom in stochastic climate prediction. Here several idealized models for stochastic climate modeling are introduced and analyzed through unambiguous mathematical theory. This analysis demonstrates the potential need for more s...

Cost-based filtering is a novel approach that combines techniques from Operations Research and Constraint Programming to filter from decision variable domains values that do not lead to better solutions [7]. Stochastic Constraint Programming is a framework for modeling combinatorial optimization problems that involve uncertainty [19]. In this work, we show how to perform cost-based filtering fo...

This paper presents a new concept to include uncertainty management in energy and environmental planning models developed in algebraic modeling languages. SETSTOCH is a tool for linking Algebraic Modeling Languages with Specialized Stochastic Programming Solvers. Its main role is to retrieve from the modeling language a dynamically ordered core model (baseline scenario) that is sent automatical...

 One of the new area of research emerging in the field of statistics is the shape analysis. Shape is defined as all the geometrical information of an object whose location, scale and orientation is not of interest. Diffusion in shape analysis can be studied via either perturbation of the key coordinates identifying the initial object or random evolution of the shape itself. Reviewing the f...

Fault zones and fault-related fracture systems control the mechanical behaviors and fluid-flow properties of the Earth’s crust. Furthermore, nowadays, modeling is being increasingly used in order to understand the behavior of rock masses, and to determine their characteristics. In this work, fault zones and fracture patterns are reviewed, and also comprehensive studies are carried out on the fr...

This paper deals with a short overview on stochastic modeling of uncertainties. We introduce the types of uncertainties, the variability of real systems, the types of probabilistic approaches, the representations for the stochastic models of uncertainties, the construction of the stochastic models using the maximum entropy principle, the propagation of uncertainties, the methods to solve the st...

We present the attributed π-calculus for modeling concurrent systems with interaction constraints depending on the values of attributes of processes. The λ-calculus serves as a constraint language underlying the π-calculus. Interaction constraints subsume priorities, by which to express global aspects of populations. We present a nondeterministic and a stochastic semantics for the attributed π-...