Sensitivity analysis quantifies the dependence of system behavior on the parameters that affect the process dynamics. Classical sensitivity analysis, however, does not directly apply to discrete stochastic dynamical systems, which have recently gained popularity because of its relevance in the simulation of biological processes. In this work, sensitivity analysis for discrete stochastic process...

To ensure efficient performance of irrigation canals, the losses from the canals need to be minimized. In this paper a modified formulation is presented to solve the optimization model for the design of different canal geometries for minimum seepage loss, in meta-heuristic environment. The complex non-linear and non-convex optimization model for canal design is solved using a probabilistic sear...

many old damaged and undamaged building structures do not meet the criteria of modern seismic design codes. such structures need to be seismically enhanced. the main objective of this paper is to propose and validate the effectiveness of an upgrade scheme for non-seismic buildings using steel plate shear walls (spsw). the upgrade is carried out considering a probability-based drift-based criter...

W a decision analyst desires a sensitivity analysis on model parameters that are estimated from data, a natural approach is to vary each parameter within one or two standard errors of its estimate. This approach can be problematic if parameter estimates are correlated or if model structure does not permit obvious standard error estimates. Both of these difficulties can occur when the analysis o...

This paper describes the probabilistic behaviour of a random Sturmian word. It performs the probabilistic analysis of the recurrence function which can be viewed as a waiting time to discover all the factors of length n of the Sturmian word. This parameter is central to combinatorics of words. Having fixed a possible length n for the factors, we let α to be drawn uniformly from the unit interva...

OBJECTIVE Markov models are the standard method used in cost-effectiveness studies to represent the natural history of disease. The objective of this study was to show the key elements in building probabilistic Markov models. METHODS We used the example of a new treatment for a generic disease. A probabilistic Markov model was constructed using statistical distributions. Monte Carlo simulatio...