Surrogate modelling under groundwater parameter uncertainty
A surrogate modelling approach based on nonlinear dimension reduction for uncertainty quantification in groundwater flow models
... Existing applications again deal with low-dimensional outputs; e.g. in Bau and Mayer (2006), the authors use a GP model to learn 4 well extraction rates for a pump-and-treat optimization problem. Our aim in this paper is ...
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Uncertainty quantification of squeal instability via surrogate modelling
... 𝐌𝐮̈ + 𝐂𝐮̇ + 𝐊𝐮 = 𝐟 𝐨𝐮𝐭 (3) where M, C and K are mass, damping and stiffness matrices, respectively. The stiffness matrix K contains contributions from the frictional forces at the contact interfaces. Due to the fact that ...
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Failure Probability Under Parameter Uncertainty
... solvency under parameter uncertainty, since it does not depend on the unknown true pa- ...risk modelling, that may be symmetric or asymmetric, with bounded or unbounded support, light- or ...
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Affine processes under parameter uncertainty
... processes under parameter uncertainty, which we call nonlinear affine ...Knightian uncertainty, especially for modelling interest rates under ...
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Modelling pesticide leaching under climate change: parameter vs climate input uncertainty
... of uncertainty. We investigated the uncertainty related to cli- mate scenario input and its importance relative to parame- ter uncertainty of the pesticide leaching ...acceptable parameter ...
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Uncertainty quantification of brake squeal Iistability via surrogate modelling
... 4. Experimental Results 66 Figure 4.4 shows the measurement setup for the friction material. The test is done under free- free boundary condition, and the roving hammer technique is used for measuring the response ...
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Evaluation of unknown groundwater contaminant sources characterization efficiency under hydrogeologic uncertainty in an experimental aquifer site by utilizing surrogate models
... unknown groundwater contaminant sources is an impor- tant but difficult step in effective groundwater ...develop surrogate models that can approximate the complex flow and transport processes in a ...
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Evaluation of Unknown Groundwater Contaminant Sources Characterization Efficiency under Hydrogeologic Uncertainty in an Experimental Aquifer Site by Utilizing Surrogate Models
... unknown groundwater contaminant sources is an impor- tant but difficult step in effective groundwater ...develop surrogate models that can approximate the complex flow and transport processes in a ...
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Parameter Estimation for Groundwater Models under Uncertain Irrigation Data
... recognitions, uncertainty in irriga- tion data is often neglected in standard groundwater model calibrations and ...to parameter and model structural ...as groundwater heads and con- taminant ...
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Groundwater Management Optimization and Saltwater Intrusion Mitigation under Uncertainty
... Using surrogate models to replace high-fidelity groundwater simulation models is key to reduce computing ...in surrogate model structure and parameters and may lead to poor accuracy in ...one ...
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Modelling and Forecasting the Yield Curve under Model uncertainty
... Abstract This paper proposes a procedure to investigate the nature and persistence of the forces governing the yield curve and to use the extracted information for forecasting purposes. The latent factors of a model of ...
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Value of Information in Design of Groundwater Quality Monitoring Network under Uncertainty
... 1: Uncertainty Analysis Groundwater flow and fate and transport modeling require sufficient data about the input parameters of hydrology and physical properties of the aquifer that is being modeled and the ...
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Optimization of maintenance policy under parameter uncertainty using portfolio theory
... That is, to choose an option depends not only on the total expected cost C( T | θ ), but also on the variance V θ (C( T | θ )). Of course, the total attitude towards risk can be taken into account, for example through ...
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Modelling and Analysing Software Requirements and Architecture Decisions under Uncertainty
... The radar model presented for the SAS model in previous pages is similar to the equations and parameter values in the GuideArch and MODA models. With respect to the decision analysis approach, radar’s analysis ...
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Modelling the dynamics of commodity prices for investment decisions under uncertainty
... Table 3.3: Parameter estimates of Schwartz (1997) two-factor model using Kalman filter. LL refers to the value of log-likelihood function. Weekly futures prices, from January 6th, 1995 to April 25th, 2008. ...
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Uncertainty handling in surrogate assisted optimisation of games
... comparisons under uncertainty (see section ...the surrogate-assisted evolutionary algorithms targeted in this thesis, this is especially relevant regarding the implementations of sampling and ...
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Modelling Surface Water-Groundwater Exchange: Evaluating Model Uncertainty from the Catchment to Bedform-Scale
... parameterized HydroGeoSphere model of the Steinlach River Test Site in southwest Germany was built as a reference. This model is then modified with simpler bathymetries, evaluating the changes to hyporheic exchange ...
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Modelling Train Station Choice under Uncertainty for Park and Ride Users
... time parameter is statistically insignificant, indicating that the differences in the marginal utilities held for the effect of travel time cannot be explained completely by the differences in these individuals’ ...
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Dynamic Incentive Contracts under Parameter Uncertainty
... project under management, can also be a source of ...how parameter and e¤ort uncertainty interact to shape the optimal design of incentive ...Does parameter uncertainty reinforce or ...
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Dynamic Incentive Contracts Under Parameter Uncertainty
... involving parameter uncertainty and described a mechanism by which uncertainty about the environment worsens the incentive in- surance ...the parameter and noise are normally ...problems ...
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