The stochastic modeling of biological systems is gaining more and more attention when stochastic fluctuations need to be described. On the other hand, the biological systems under investigation become much more complex than before. Traditional modeling methods like stochastic Petri nets do not easily scale and thus become difficult to tackle this situation. This paper aims to present a colored ...

The use of artificial neural networks has increased in many areas of engineering. In particular, this method has been applied to many geotechnical engineering problems and demonstrated some degree of success. A review of the literature reveals that it has been used successfully in modeling soil behavior, site characterization, earth retaining structures, settlement of structures, slope stabilit...

Analytical modeling is a crucial part in the analysis and design of computer systems. Stochastic Petri Nets represent a powerful tool, widely used for dependability, performance and performability modeling. Many structural and stochastic extensions have been proposed so as to increase their modeling power. In this paper we review the main structural and stochastic extensions of Petri nets, by p...

Since the emergence of power market, the target of power generating utilities has mainly switched from cost minimization to revenue maximization. They dispatch their power energy generation units in the uncertain environment of power market. As a result, multi-stage stochastic programming has been applied widely by many power generating agents as a suitable tool for dealing with self-scheduling...

Stochastic behavior—the probabilistic evolution of a system in time—is essential to modeling the complexity of real-world systems. It enables realistic performance modeling, quality-of-service guarantees, and especially simulations for biological systems. Languages like the stochastic pi calculus have emerged as effective tools to describe and reason about systems exhibiting stochastic behavior...

We introduce an extension of the classic Discrete Event System Specification (DEVS) formalism that includes stochastic features. Based on the use of the probability spaces theory we define the stochastic DEVS (STDEVS) specification, which provides a formal framework for modeling and simulation of general non-deterministic discrete event systems. The main theoretical properties of the STDEVS fra...

ISSN: 0736-2994 (Print) 1532-9356 (Online) Journal homepage: http://www.tandfonline.com/loi/lsaa20 Modeling stochastic anomalies in an SIS system Andrew Vlasic & Troy Day To cite this article: Andrew Vlasic & Troy Day (2017) Modeling stochastic anomalies in an SIS system, Stochastic Analysis and Applications, 35:1, 27-39, DOI: 10.1080/07362994.2016.1216320 To link to this article: http://dx.doi...

We propose stochastic process models as a means for studying and rendering unbounded biological structures, involving mechanisms that extend over geometric space. As an example, we discuss a case study of actin polymerization dynamics, which plays a key role in many cellular activities and enjoys a rich structure.Weprovide a comparative reviewof various approaches in the literature formodeling ...

Standard credit risk models rely on a doubly stochastic structure. Conditional on the evolution of common factors, defaults are independent. Recently, tests by Das, Duffie, Kapadia and Saita (2007) have cast doubt on the empirical validity of this assumption. We modify their estimation approach in two ways. First, we model intra-month patterns in observed defaults. Second, we estimate default i...