Results 21 to 30 of about 3,014,362 (294)
Statistical Science, 2004 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Clyde, Merlise, George, Edward I
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Uncertainty Analysis of Neutron Diffusion Eigenvalue Problem Based on Reduced-order Model
Yuanzineng kexue jishu, 2023 In order to improve the efficiency of core physical uncertainty analysis based on sampling statistics, the proper orthogonal decomposition (POD) and Galerkin projection method were combined to study the application feasibility of reduced-order model ...
In order to improve the efficiency of core physical uncertainty analysis based on sampling statistics, the proper orthogonal decomposition (POD) and Galerkin projection method were combined to study the application feasibility of reduced-order model based on POD-Galerkin method in core physical uncertainty analysis. The two-dimensional two group TWIGL benchmark question was taken as the research object, the key variation characteristics of the core flux distribution were extracted under the finite perturbation of the group constants of each material region, and the full-order neutron diffusion problem was projected on the variation characteristics to establish a reduced-order neutron diffusion model. The reduced-order model was used to replace the full-order model to carry out the uncertainty analysis of the group constants of the material region. The results show that the bias of the mathematical expectation of keff calculated by reduced-order and full-order models is close to 1 pcm. In addition, compared with the calculation time required for uncertainty analysis of full-order model, the analysis time of reduced-order model (including the calculation time of the full-order model required for the construction of reduced-order model) is only 11.48%, which greatly improves the efficiency of uncertainty analysis. The biases of mathematical expectation of keff calculated by reduced-order and full-order models based on Latin hypercube sampling and simple random sampling are less than 8 pcm, and under the same sample size, the bias from the Latin hypercube sampling result is smaller. From the TWIGL benchmark test results, under the same sample size, Latin hypercube sampling method is more recommended for POD-Galerkin reduced-order model.
doaj
Assessment of model bias of SPT, Vs and CPT-based liquefaction models
Yantu gongcheng xuebao, 2023 The liquefaction models established through the in-situ tests and liquefaction case histories are widely adopted in the liquefaction evaluation of a site.
SHEN Mengfen , BAO Lichun , SUN Honglei , CAI Yuanqiang
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On the relationship between aerosol model uncertainty and radiative forcing uncertainty [PDF]
Proceedings of the National Academy of Sciences of the United States of America, 2016 Lindsay Lee +2 more
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Managing structural uncertainty in health economic decision models: a discrepancy approach [PDF]
, 2012 Healthcare resource allocation decisions are commonly informed by computer model predictions of population mean costs and health effects. It is common to quantify the uncertainty in the prediction due to uncertain model inputs, but methods for ...
Bernardo +21 more
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Model Uncertainty: A Reverse Approach
SIAM Journal on Financial Mathematics, 2022 Robust models in mathematical finance replace the classical single probability measure by a sufficiently rich set of probability measures on the future states of the world to capture (Knightian) uncertainty about the "right" probabilities of future events.
Felix-Benedikt Liebrich +2 more
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Risk, Unexpected Uncertainty, and Estimation Uncertainty: Bayesian Learning in Unstable Settings [PDF]
, 2011 Recently, evidence has emerged that humans approach learning using Bayesian updating rather than (model-free) reinforcement algorithms in a six-arm restless bandit problem. Here, we investigate what this implies for human appreciation of uncertainty.
A Quinn +49 more
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Embedded model control, performance limits: A case study
Dyna, 2017 This paper presents the analysis and implementation of two control laws applied on a case study. The first one and main focus of this work is the Embedded Model Control whose main characteristics are the active disturbance rejection and uncertainties ...
Wilber Acuña-Bravo +2 more
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IEEE Access, 2023 This paper investigates the adaptive control problem for a class of Euler-Lagrangian (EL) systems with uncertain parameters and external disturbances.
Bowen Zhang, Tong Wu, Tianqi Wang
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Assessment of flood damages and benefits of remedial actions: "What are the weak links?"; with application to the Loire [PDF]
, 1995 Flood damage models are used to determine the impact of measures to reduce damage due to river flooding. Such models are characterized by uncertainty. This uncertainty may affect the decisions made on the basis of the model outcomes.
Blois, C.J. de, Wind, H.G.
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