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Green Simulation with Database Monte Carlo
ACM Transactions on Modeling and Computer Simulation, 2016In a setting in which experiments are performed repeatedly with the same simulation model, green simulation means reusing outputs from previous experiments to answer the question currently being asked of the model. In this article, we address the setting in which experiments are run to answer questions quickly, with a time limit providing a fixed ...
Mingbin Feng, Jeremy Staum
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Monte Carlo simulation on microcomputers
SIMULATION, 1992Monte Carlo analysis is a practical tech nique for including the effects of uncertainty in a model intended for decision support. It has been infrequently used, however, perhaps because it has been tedious and boring to do. A recently available software add-in to 1-2-3 named @Risk makes Monte Carlo analysis much easier.
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Overrelaxation and Monte Carlo simulation
Physical Review D, 1987I study a simple variation of the algorithm of Metropolis et al. for simulating statistical systems. The trial changes in any given variable are taken from a region of phase space far from the old value but involving only small changes in energy. This results in correlation times which are short compared to the usual applications of the algorithm of ...
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2019
The sequential use of random numbers, to sample the values of probability variables, allows obtaining solutions to mathematical problems such as the Monte Carlo method, that allows to model stochastic parameters or deterministic based on random sampling.
Lorenzo Cevallos-Torres +1 more
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The sequential use of random numbers, to sample the values of probability variables, allows obtaining solutions to mathematical problems such as the Monte Carlo method, that allows to model stochastic parameters or deterministic based on random sampling.
Lorenzo Cevallos-Torres +1 more
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Multicanonical Monte Carlo Simulations
International Journal of Modern Physics C, 1993The multicanonical ensemble is reviewed. Simulations of this ensemble promise improvements for a wide range of systems. Applications to first order phase transitions and spin glasses are summarized.
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Monte Carlo simulation in Fourier space
Computer Physics Communications, 2008zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Bayesian post-processing of Monte Carlo simulation in reliability analysis
Reliability Engineering and System Safety, 2022Wolfgang Betz +2 more
exaly
2020
In this chapter, we describe the Monte Carlo (MC) simulation used in this analysis. The purposes of the MC simulation are to estimate the signal acceptance for the \(K_L \!\rightarrow \! \pi ^0 \nu \overline{\nu }\) and \(K_L \!\rightarrow \! \pi ^0 X^0\) decays the acceptance for the normalization mode decays, namely \(K_L \!\rightarrow \! 3\
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In this chapter, we describe the Monte Carlo (MC) simulation used in this analysis. The purposes of the MC simulation are to estimate the signal acceptance for the \(K_L \!\rightarrow \! \pi ^0 \nu \overline{\nu }\) and \(K_L \!\rightarrow \! \pi ^0 X^0\) decays the acceptance for the normalization mode decays, namely \(K_L \!\rightarrow \! 3\
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