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[PDF] Top 20 Monte Carlo method and sensitivity estimations

Has 10000 "Monte Carlo method and sensitivity estimations" found on our website. Below are the top 20 most common "Monte Carlo method and sensitivity estimations".

Monte Carlo method and sensitivity estimations

Monte Carlo method and sensitivity estimations

... geometries and=or complex spectral properties ...low-cost sensitivity computations can be easily associated with Monte Carlo methods, provided that the underlying integral formulation is ... Voir le document complet

11

Monte-Carlo and sensitivity transport models for domain deformation

Monte-Carlo and sensitivity transport models for domain deformation

... the sensitivity Monte-Carlo weight has a non null value: when γ hits the square,  u  is outgoing, and γ  hits the ...results and illustrate the stabil- ity of sensitivities estimated ... Voir le document complet

14

OECD/NEA intercomparison of deterministic and monte carlo cross-section sensitivity codes using sneak-7 benchmarks

OECD/NEA intercomparison of deterministic and monte carlo cross-section sensitivity codes using sneak-7 benchmarks

... Deterministic and Monte Carlo Cross-Section Sensitivity Codes Using SNEAK-7 Benchmarks PHYSOR 2016 – Unifying Theory and Experiments in the 21st Century Sun Valley, Idaho, USA, May 1 – ... Voir le document complet

11

Algorithms and applications of the Monte Carlo method : Two-dimensional melting and perfect sampling

Algorithms and applications of the Monte Carlo method : Two-dimensional melting and perfect sampling

... automata and for Markov-chain ...time, and remain indistinguishable from then on. For Markov- chain Monte Carlo algorithms, the closely related case where the entire space of initial ... Voir le document complet

161

A boundary-based net-exchange Monte Carlo method for absorbing and scattering thick media

A boundary-based net-exchange Monte Carlo method for absorbing and scattering thick media

... the method, in particular its strict analogy with physical processes, and the ability to solve complex problems, while trying to improve convergence ...changes and adaptation of sampling laws ... Voir le document complet

25

Clock Monte Carlo methods

Clock Monte Carlo methods

... Science and Technology of China, Hefei, Anhui 230026, China (Dated: October 17, 2019) We propose the clock Monte Carlo technique for sampling each successive chain step in constant ...filter ... Voir le document complet

7

A New Walk on Equations Monte Carlo Method for Linear Algebraic Problems

A New Walk on Equations Monte Carlo Method for Linear Algebraic Problems

... tests and discussion In this section we show numerical tests divided into several ...that Monte Carlo methods are very efficient to deal with large and very large ... Voir le document complet

31

Optimized Population Monte Carlo

Optimized Population Monte Carlo

... Population Monte Carlo V´ıctor Elvira and ´ Emilie Chouzenoux Abstract—Adaptive importance sampling (AIS) methods are increasingly used for the approximation of distributions and related ... Voir le document complet

13

Monte Carlo Method Applied to the ABV Model of an Interconnect Alloy

Monte Carlo Method Applied to the ABV Model of an Interconnect Alloy

... modeled and simulated by ...distribution and size of defects, with a maximum temperature localized above the larger ...evolution and mapping of ... Voir le document complet

6

Addressing nonlinearities in Monte Carlo

Addressing nonlinearities in Monte Carlo

... 1,2 Monte Carlo is famous for accepting model extensions and model refinements up to infinite ...basis and increasing the configuration space ...particles, and concentrated solar power ... Voir le document complet

12

Monte-Carlo and Domain-Deformation Sensitivities

Monte-Carlo and Domain-Deformation Sensitivities

... The sensitivity model has been also cross-validated with deformation velocity method on academical ...density and its shape sensitivity for a different set of ... Voir le document complet

9

A regression Monte-Carlo method for Backward Doubly Stochastic Differential Equations

A regression Monte-Carlo method for Backward Doubly Stochastic Differential Equations

... 1. Introduction Since the pioneering work of E. Pardoux and S. Peng [11], backward stochastic dif- ferential equations (BSDEs) have been intensively studied during the two last decades. Indeed, this notion has ... Voir le document complet

39

Monte Carlo advances and concentrated solar applications

Monte Carlo advances and concentrated solar applications

... following: Monte Carlo methods are sometimes computationally expensive, but they can provide additional information concerning the influence of free design ...of sensitivity weights is com- monly ... Voir le document complet

30

Pépite | Méthodes quasi-Monte Carlo et Monte Carlo : application aux calculs des estimateurs Lasso et Lasso bayésien

Pépite | Méthodes quasi-Monte Carlo et Monte Carlo : application aux calculs des estimateurs Lasso et Lasso bayésien

... adjust the proposal such that the acceptance rate is around 1 2 for one or two dimensional target distributions, and around 1 4 for larger dimensions. Haario et al. [ 9 ] suggested a method called Adaptive ... Voir le document complet

107

An Overview of Cloud Simulation Enhancement using the Monte-Carlo Method

An Overview of Cloud Simulation Enhancement using the Monte-Carlo Method

... IV. E VALUATION Using this model, we ran a 500-iteration MCS for each strategy. The resulting distributions are shown in Figure 2. The makespan density graph shows the simulation result distribution as filled curves ... Voir le document complet

3

A new Monte Carlo method for neutron noise calculations

A new Monte Carlo method for neutron noise calculations

... two Monte Carlo methods with the deterministic methods (diffusion and transport) in case of a heterogenous one-dimensional system with 4 energy groups and 6 precursor ...cm) and we ... Voir le document complet

7

Population Monte Carlo

Population Monte Carlo

... dependence and starting values, as shown in this paper. The population Monte Carlo principle we describe here consists of iterated generations of importance samples, with importance functions ... Voir le document complet

23

A hamiltonian Monte Carlo method for non-smooth energy sampling

A hamiltonian Monte Carlo method for non-smooth energy sampling

... I2M and CNRS UMR 7373, Aix-Marseille University, Marseille Cedex, France (e-mail: ...chain Monte Carlo (MCMC) sampling techniques ...Hamiltonian Monte Carlo (HMC) sampling technique has ... Voir le document complet

11

Monte-Carlo Hex

Monte-Carlo Hex

... different method that uses Monte-Carlo ...tried Monte-Carlo meth- ods with Hex, we did not use tree search and ...for Monte-Carlo methods for Hex raised with the ... Voir le document complet

9

Line-sampling-based Monte Carlo method

Line-sampling-based Monte Carlo method

... For each case, the considered quantity is the spectrally integrated intensity at location x 0 resulting from the emission/absorption of the gaseous column [0, x 0 ]. The considered range for spectral integration is [10 − ... Voir le document complet

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