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» Dependence Modeling for Stochastic Simulation
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WSC
1998
13 years 8 months ago
Integrating Neural Networks with Special Purpose Simulation
Traditional methods of dealing with variability in simulation input data are mainly stochastic. This is most often the best method to use if the factors affecting the variation or...
Dany Hajjar, Simaan M. AbouRizk, Kevin Mather
WSC
2001
13 years 8 months ago
Monte Carlo simulation approach to stochastic programming
Various stochastic programmingproblemscan be formulated as problems of optimization of an expected value function. Quite often the corresponding expectation function cannot be com...
Alexander Shapiro
QEST
2007
IEEE
14 years 1 months ago
The PEPA Plug-in Project
We present a GUI-based tool supporting the stochastic process algebra PEPA with modules for performance evaluation through Markovian steady-state analysis, fluid flow analysis, ...
Mirco Tribastone
WSC
2007
13 years 9 months ago
Finite-sample performance guarantees for one-dimensional stochastic root finding
We study the one-dimensional root finding problem for increasing convex functions. We give gradient-free algorithms for both exact and inexact (stochastic) function evaluations. ...
Samuel Ehrlichman, Shane G. Henderson