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» Modeling Dependencies in Stochastic Simulation Inputs
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WSC
2001
13 years 6 months ago
Accounting for input model and parameter uncertainty in simulation
Taking into account input-model, input-parameter, and stochastic uncertainties inherent in many simulations, our Bayesian approach to input modeling yields valid point and confide...
Faker Zouaoui, James R. Wilson
CLIMA
2004
13 years 6 months ago
The Apriori Stochastic Dependency Detection (ASDD) Algorithm for Learning Stochastic Logic Rules
Apriori Stochastic Dependency Detection (ASDD) is an algorithm for fast induction of stochastic logic rules from a database of observations made by an agent situated in an environm...
Christopher Child, Kostas Stathis
JCNS
2002
72views more  JCNS 2002»
13 years 5 months ago
Noise and the PSTH Response to Current Transients: II. Integrate-and-Fire Model with Slow Recovery and Application to Motoneuron
A generalized version of the integrate-and-fire model is presented that qualitatively reproduces firing rates and membrane trajectories of motoneurons. The description is based on ...
Alix Herrmann, Wulfram Gerstner
WSC
2001
13 years 6 months ago
Resampling methods for input modeling
Stochastic simulation models are used to predict the behavior of real systems whose components have random variation. The simulation model generates artificial random quantities b...
Russell R. Barton, Lee Schruben
WSC
1997
13 years 6 months ago
Seven Habits of Highly Successful Input Modelers
Discrete-event simulation models typically have stochastic components that mimic the probabilistic nature of the system under consideration. Successful input modeling requires a c...
Lawrence Leemis