Sciweavers

Free Online Productivity Tools i2Speak i2Symbol i2OCR iTex2Img iWeb2Print iWeb2Shot i2Type iPdf2Split iPdf2Merge i2Bopomofo i2Arabic i2Style i2Image i2PDF iLatex2Rtf Sci2ools

12

MMAS
2010
Springer

favoriteEmaildiscussreport

117views Intelligent Agents» more MMAS 2010»

Markov Chain Stochastic Parametrizations of Essential Variables

12 years 11 months ago

Markov Chain Stochastic Parametrizations of Essential Variables

Download www.math.uh.edu

We analyze the performance of the novel Markov chain stochastic modeling technique for derivation of effective equations for a set of essential variables. This technique is an empirical approach where the right-hand side of the essential variables is modeled by a Markov chain. We demonstrate that the Markov chain modeling approach performs well in a prototype model without scale separation between the essential and the nonessential variables. Moreover, we utilize the truncated Burgers

K. Nimsaila, I. Timofeyev

Real-time Traffic

Essential Variables | Intelligent Agents | Markov Chain | MMAS 2010 | Stochastic Parametrization Ams |

claim paper

Related Content

» Stochastic Bounds Applied to the End to End QoS in Communication Systems

» Hybrid Numerical Solution of the Chemical Master Equation

» Iterative Markov Chain Monte Carlo Computation of Reference Priors and Minimax Risk

» A dynamic Bayesian network to represent discrete duration models

» A Precedence PEPA Model for Performance and Reliability Analysis

» The Infinite Factorial Hidden Markov Model

» Adaptive Online Multistroke Sketch Recognition Based on Hidden Markov Model

» Parallelizable Sampling of Markov Random Fields

» Extended Directed Search for Probabilistic Timed Reachability

Post Info
More Details (n/a)

Added	20 May 2011
Updated	20 May 2011
Type	Journal
Year	2010
Where	MMAS
Authors	K. Nimsaila, I. Timofeyev

Comments (0)