Surrogate Model
A surrogate model for simulation–optimization of aquifer systems subjected to seawater intrusion
... results are investigated based on the developed EPR-GA approach. In the first study of sensitivity analysis, results show the positive impacts of the increasing recovery ratios on the overall trend of the Pareto ...
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Efficient Computation and Uncertainty Analysis of Underwater Acoustic Propagation based on Kriging Surrogate Model
... acoustic model is directly used as a forward model under the Monte Carlo framework, it will require a lot of calculation cost, which is not desirable in practical ...Kriging surrogate model ...
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Design optimization of stent and its dilatation balloon using kriging surrogate model
... Kriging surrogate model is proposed to optimize geometries of stent and length of stent dilatation balloon step by ...Kriging surrogate model coupled with design of experiment method is ...
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Subspace Methods applied to gPC-based Surrogate Model Construction.
... that surrogate model techniques must be improved to allow one execute engineering applica- tions such as uncertainty quantification in a practical ...
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Optimal Design of Photonic Band-Gap Structure Based on Kriging Surrogate Model
... Kriging surrogate model can effectively reduce the transmission coefficient in the desired frequency band to improve maximize the photonic band-gap of the PBG ...
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Multi-objective optimization of coronary stent using Kriging surrogate model
... The absolute value of dogboning ratio and radial elastic recoil of Palmaz-Schatz stent were minimized by the multi-objective optimization method proposed in this paper. The initial trial samples which included the ...
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A Surrogate Model-based Framework for Design and Macromodeling of Self-calibrated Analog Circuits.
... for model construction with SUMO ...a surrogate-model expression describing the circuit’s performance in terms of the design parameters and the variations are ...The model expression will be ...
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Surrogate model for probabilistic modeling of atmospheric entry for small NEO's
... In this work a new method for UP is used and compared to the results given by MC. The used approach decomposes the stochastic space into sub-domains, which are then interpolated separately by a selected interpolation ...
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Moment based metrics for global sensitivity analysis of hydrological systems
... desired model output, ...more) model input parameter(s), of the expected value, vari- ance, skewness and kurtosis of ...uncertain model param- ...full model response through a surrogate ...
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Data assimilation as a learning tool to infer ordinary differential equation representations of dynamical models
... reference model from its observation using Bayesian data assimilation, which is a new and original scope for data ...the surrogate model. We have chosen the surrogate model to be the ...
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Development of a Fast Urban Flood Model for Real-Time Applications
... The surrogate model emulates the results of the 1D/2D model much closer in regions R1, R2 and ...the surrogate model succeeds in predicting the moment of inundation correctly, but ...
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A Review on Surrogate-Based Global Optimization Methods for Computationally Expensive Functions
... (DOE), surrogate modeling techniques, infill criteria and design space reduction are the key issues which arise in surrogate-based global ...first surrogate model. It’s no doubt that the ...
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Parameterization Of The Exhaust-Fascia Interface Using Surrogate Modelling
... Highest fascia temperatures were predicted by the surrogate model to occur at low speed and high load. In reality, a vehicle will very rarely sit stationary at wide open throttle for the amount time ...
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Simulating Non-Dilute Transport in Porous Media Using a Thermodynamically Constrained Averaging Theory-Based Model
... appropriate model responses, we use the set of training points to determine the surrogate model ...A surrogate for the lowest concentration non-tracer experiment, Column 11, B11, was first ...
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Generating physics based 1D surrogate models from 2D model results
... physics-based surrogate models have mostly gone unexplored (Fernández-Godino et ...river model is lumped into storage cells, and the cell state and inter-cell fluxes are approximated with data-driven ...
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Multiple Tensor Train Approximation of Parametric Constitutive Equations in Elasto-Viscoplasticity
... construct surrogate models of parametric Differential Algebraic Equations based on a tensor representation of the ...reference model, an approximation given in tensor-train ...constructed surrogate ...
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Statistical emulation of a tsunami model for sensitivity analysis and uncertainty quantification
... tsunami model developed by Sammarco and Renzi (2008) has been obtained using the Outer Product ...This surrogate model is built using a combination of prior knowl- edge about the simulator, ...
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Evaluation of Unknown Groundwater Contaminant Sources Characterization Efficiency under Hydrogeologic Uncertainty in an Experimental Aquifer Site by Utilizing Surrogate Models
... GPR-based surrogate model for source characterization is also evaluated by using the same testing ...GPR-based surrogate models for test- ing data in terms of NAEE are equal to ...SOM-based ...
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Adaptive surrogate modeling for response surface approximations with application to bayesian inference
... adaptive surrogate models using a posteriori error estimates for quantities of interest can significantly reduce the computational cost in problems of statistical ...As surrogate models provide only ...
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Variable-Fidelity Design Optimization of Microwave Devices Using Multi-Dimensional Cauchy Approximation and Coarsely Discretized Electromagnetic Models
... of surrogate model optimization and, especially, parameter extraction, starts playing important role in the total cost of SM optimization and may even determine ...EM-based model may have poor ...
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