Monte Carlo approximation method
RISK ASSESSMENT WITH THE USE OF THE MONTE-CARLO METHOD
... Purpose. This work involves the development of a numerical model for the calculation of chemical contamina- tion zones in the event of ammonia accident at the pumping station, as well as a model for assessing the risk of ...
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Multilevel and quasi Monte Carlo methods for uncertainty quantification in particle travel times through random heterogeneous porous media
... expansion method [2,13–16,21,22]. This method provides an approximation (due to the truncation of an infinite series) of the permeability fields at all the points of the continuous domain, which can ...
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Multi asset Spread Option Pricing and Hedging
... closed-form approximation formula for the efficient pricing of two-asset spread ...integration method, numerical solutions to partial differential equations and Monte Carlo simulation, become ...
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Energetics and dipole moment of transition metal monoxides by quantum Monte Carlo
... The dipole moment appears to be more challenging and requires a complicated treatment of the wave function nodes to obtain a stable value with respect to changes in the nodes. We have obtained a converged value for TiO, ...
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An Interactive Framework for The Parameter Design Problem
... a method by which the user can manually change the values of µ 1 ...series approximation method or Monte-Carlo simulation as appropriate and as we explain in Chapter ...
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On Solving a System of Volterra Integral Equations with Relaxed Monte Carlo Method
... simulation method was used for treatment of systems of Volterra integral equations of the second ...relaxed Monte Carlo method with im- portance sampling and numerical approximation ...
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Applications of the Fixed-node Quantum Monte Carlo Method.
... In conclusion, we have carried out QMC study focused on calcu- lation of the vertical excitation energy of Zn-porphyrin. The DMC calculations were performed in the framework of the fixed-node approximation. The ...
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Comparison of the Bayesian Methods on Interval Censored Data for Weibull Distribution
... Lindley’s approximation and Markov Chain Monte Carlo, where the Metropolis-Hastings algorithm used to estimate the scale and shape parameters, the mean squared errors (MSE) for each method ...
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RISK ASSESSMENT WITH THE USE OF THE MONTE-CARLO METHOD
... Purpose. This work involves the development of a numerical model for the calculation of chemical contamina- tion zones in the event of ammonia accident at the pumping station, as well as a model for assessing the risk of ...
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A hierarchical finite element Monte Carlo method for stochastic two scale elliptic equations
... the Monte Carlo method, we need to consider many uncorrelated real- izations to accurately approximate the ...element approximation and the Monte Carlo method to compute ...
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A Study of the Errors of the Fixed-Node Approximation in Diffusion Monte Carlo.
... Diffusion Monte Carlo (DMC) is one of a class of methods known as “projector methods,” so-called because it has the ability to project out eigenstates from the trial wave ...an approximation (the ...
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Mean exit times and the multilevel Monte Carlo method
... existing approximation results that are relevant to our ...standard Monte Carlo, defines a multilevel algorithm, and shows that it offers improved ...
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Multi level Monte Carlo methods for the approximation of invariant measures of stochastic differential equations
... The rest of the paper is organised as follows: In Sect. 2 we describe the standard MLMC framework, discuss the con- tracting properties of the true trajectories of (2) and describe an algorithm for applying MLMC with ...
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Multiple particle filtering for tracking wireless agents via Monte Carlo likelihood approximation
... Additional simulation results, in which the agents’ motion is obtained via computational fluid dynamics (CFD) simu- lations, are presented. In contrast to the results presented in the context of the first simulation ...
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Recent advances in various fields of numerical probability*,**
... Multilevel Monte-Carlo method which, among other fields of applications, is a very efficient method for the approximation of diffusion processes, we focus on some adaptive multilevel ...
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Phase Space Path Integral Representation for Wigner Function
... harmonic approximation and Monte Carlo method allowing numerical calcu- lation of Wigner function, distribution functions and average quantum values has been ...related Monte ...
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TESTING HISTOLOGICAL IMAGES OF MAMMARY TISSUES ON COMPATIBILITY WITH THE BOOLEAN MODEL OF RANDOM SETS
... a Monte Carlo method based on the approximation of the envelopes by a multi-normal distribution with the normalized intrinsic volume densities of parallel sets as a summary statistics had the ...
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Analysing multi-level Monte Carlo for options with non-globally Lipschitz payoff
... Monte Carlo experiment. From the perspective of a confidence interval width, this error is O(1/ √ N ) [5]. Overall, we may regard µ as giving an accuracy of O(h) + O(1/ √ N ). To achieve a target accuracy ...
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Quasi Monte Carlo and multilevel Monte Carlo methods for computing posterior expectations in elliptic inverse problems
... It would be interesting to compare the performance of the ratio estimators considered in this work to Markov chain Monte Carlo (MCMC) and multilevel Markov chain Monte Carlo (MLM- CMC) methods ...
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Ultra-fast Carrier Transport Simulation on the Grid. Quasi-Random Approach
... of Monte Carlo applications makes efficient use of Grid ...(distributed) Monte Carlo applications require that the underlying random number streams in each subtask are independent in a ...
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