Results 21 to 30 of about 547,284 (267)
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
Model uncertainty – parameter uncertainty versus conceptual models
Water Science and Technology, 2005 Uncertainties in model structures have been recognised often to be the main source of uncertainty in predictive model simulations. Despite this knowledge, uncertainty studies are traditionally limited to a single deterministic model and the uncertainty addressed by a parameter uncertainty study.
A L, Højberg, J C, Refsgaard
openaire +2 more sources
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
doaj +1 more source
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
doaj +1 more source
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
doaj +1 more source
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
openaire +4 more sources
Atmosphere, 2021 The projected ISM precipitation changes under low-emission scenarios, Representative Concentration Pathway 2.6 (RCP2.6) and Shared Socioeconomic Pathway 1-2.6 (SSP1-2.6), are investigated by outputs from models participating in phases 5 and 6 of the ...
Shang-Min Long, Gen Li
doaj +1 more source
An Entropic Approach for Pair Trading
Entropy, 2017 In this paper, we derive the optimal boundary for pair trading. This boundary defines the points of entry into or exit from the market for a given stock pair.
Daisuke Yoshikawa
doaj +1 more source
Forecasting the Crude Oil Spot Price with Bayesian Symbolic Regression
Energies, 2022 In this study, the crude oil spot price is forecast using Bayesian symbolic regression (BSR). In particular, the initial parameters specification of BSR is analysed.
Krzysztof Drachal
doaj +1 more source
Time-Varying Window Length for Correlation Forecasts
Econometrics, 2017 Forecasting correlations between stocks and commodities is important for diversification across asset classes and other risk management decisions. Correlation forecasts are affected by model uncertainty, the sources of which can include uncertainty about
Yoontae Jeon, Thomas H. McCurdy
doaj +1 more source