Monte Carlo uncertainty analysis
Topological analysis in Monte Carlo simulation for uncertainty propagation
... comparative analysis step in ...reduce uncertainty on a per-scenario basis and (iii) enable targeted improvement of the model by comparing data lever- age between ...
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Efficient Computation and Uncertainty Analysis of Underwater Acoustic Propagation based on Kriging Surrogate Model
... the Monte Carlo simulation is also used to analyze the uncertainty of acoustic propagation loss, in terms of the posterior probability density ...the uncertainty of transmission ...
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Multilevel and quasi Monte Carlo methods for uncertainty quantification in particle travel times through random heterogeneous porous media
... The analysis was focused on employing the four methods to solve, under the same conditions, a stochastic model defined in a high-dimensional probability space, and in comparing the computational costs incurred by ...
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Statistical analysis of weibull estimation uncertainty for crack initiation testing through Monte Carlo simulation
... To obtain the model parameters of SCC initiation (i.e., Weibull parameters in this case), a cracking test must be performed. The typical procedure of a cracking test involves an interval-censored reliability test. This ...
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Exploring uncertainty in glacier mass balance modelling with Monte Carlo simulation
... calculated uncertainty to be approximately 10% of to- tal melt at one particular point on one ...of uncertainty in the latter was applied and thus, the uncertainty model can not yet be applied to an ...
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A Bayesian Monte-Carlo Uncertainty Model for Assessment of Shear Stress Entropy
... The uncertainty analysis of many hydraulic and hydrological models has been tackled by many researchers using various uncertainty methods ...Likelihood Uncertainty Estimation (GLUE) to measure ...
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Examples of Monte Carlo techniques applied for nuclear data uncertainty propagation
... For the MC approach, the nuclear data are sampled at the beginning of the simulation, then the reactor core simulator that solves coupled multi-physics at different levels of approximation is executed. In this work, we ...
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Reduction of Monte Carlo simulation runs for uncertainty estimation in hydrological modelling
... Monte-Carlo (MC) simulation based techniques are often applied for the estimation of uncertainties in hydrological models due to uncertain parameters. One such technique is the Generalised Likelihood ...
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Evaluation of Dutch election programs: The impact of parameter uncertainty
... the Monte Carlo method is that it may be time consuming and complicated for large economic models used by the ...performed Monte Carlo analyses with large economic models such as JADE, MIMIC ...
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Validation and uncertainty estimation of an analytical method for the determination of phenolic compounds in concrete
... by Monte Carlo simulation from the distribution assigned to the measured and through GUM analysis is shown in ...from Monte Carlo simulations are skewed to the right and their coverage ...
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Uncertainty and energy-sector equity returns in Iran: a Bayesian and quasi-Monte Carlo time-varying analysis
... The analysis specifically considers the refining, drilling, and petrochemical equity sectors of the Tehran Stock ...quasi-Monte Carlo and Bayesian optimization methods in the framework of a ...
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Comparison of the Gum and Monte Carlo Methods for the Uncertainty Estimation in Electromagnetic Compatibility Testing
... conventional uncertainty analysis, stated in the Guide to the Expression of Uncertainty in Measurement (GUM) [4], is often difficult to implement in complex systems, such as EMC test systems, and ...
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MONTE CARLO SIMULATIONS FOR UNCERTAINTY QUANTIFICATION: MATHEMATICAL FOUNDATION AND IMPLICATION OF UNDERLYING ASSUMPTIONS
... Monte Carlo simulation is refers to simulation that utilizes random number and statistical analysis to compute ...context, Monte Carlo simulation is considered a methodical way of doing ...
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Monte Carlo simulation for uncertainty estimation on structural data in implicit 3-D geological modeling, a guide for disturbance distribution selection and parameterization
... input uncertainty is critical to the propagation of uncertainty in ...of uncertainty that stems from the necessarily imperfect mod- eling engine ...variographic analysis (Appendix C, ...own ...
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Uncertainty Estimation in Complex Permittivity Measurements by Shielded Dielectric Resonator Technique Using the Monte Carlo Method
... Exact relations among permittivity, sample and cavity dimensions, measured resonant frequency and the unloaded Q-factor can only be derived if we can carry out an accurate theoretical analysis for the resonant ...
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Sensitivity and uncertainty analysis of βeff for MYRRHA using a Monte Carlo technique
... this analysis, we employed eight parameters: fi ssion, neutron capture, elastic scattering, inelastic scattering, and (n, 2n) reaction cross sections for major constituent materials: U, Pu, 241 Am, 16 O, 56 Fe, Pb, ...
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Model and distribution uncertainty in multivariate GARCH estimation: a Monte Carlo analysis
... The Monte Carlo analysis is motivated by the fact that the precision of the ex-post analysis is affected by the observability of the true volatilities which are indeed unobservable on the ...
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Uncertainty analysis for a wave energy converter: the Monte Carlo method
... include calibration data or previous measurement data, experience, manufacturers’ specifications, uncertainties assigned to reference data, or any other reliable source of information. It is also important to identify ...
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Efficient use of Monte Carlo: the fast correlation coefficient
... In reference [12], the TMC method was used to calculate the full covariance matrix of a neutron spectrum. For this MCNP and 300 TENDL2015 random fi les were used. The covariance matrix was subsequently used when adjusting ...
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Research on Stackelberg Model of Power Market Considering Interruptible Load Contract
... for the original model considering the interruptible load contract, and the market demand model based on the wholesale market building Stackelberg model. The original market model is no longer smooth, so a new method for ...
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