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Active learning to understand infectious disease models and improve policy making. [PDF]
PLoS Computational Biology, 2014 Modeling plays a major role in policy making, especially for infectious disease interventions but such models can be complex and computationally intensive. A more systematic exploration is needed to gain a thorough systems understanding.
Lander Willem +5 more
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Influence of diesel surrogates on the behavior of simplified spray models [PDF]
, 2012 Numerous experimental investigations make use of diesel surrogates to make the computational time reasonable. In the few studies where measured (surrogate and real diesel) and computed (surrogate only) results have been compared, the selection ...
F Battin-Leclerc +6 more
core +2 more sources
, 2020 Bayesian inverse modeling is important for a better understanding of hydrological processes. However, this approach can be computationally demanding, as it usually requires a large number of model evaluations.
Chen, Dingjiang +4 more
core +1 more source
Multifidelity Surrogate Models for Efficient Uncertainty Propagation Analysis in Salars Systems
Frontiers in Water, 2022 Salars are complex hydrogeological systems where the high-density contrasts require advanced numerical models to simulate groundwater flow and brine transport.
Vasileios Christelis, Andrew G. Hughes
doaj +1 more source
Fast and accurate prediction of numerical relativity waveforms from binary black hole coalescences using surrogate models [PDF]
, 2015 Simulating a binary black hole (BBH) coalescence by solving Einstein's equations is computationally expensive, requiring days to months of supercomputing time.
Blackman, Jonathan +6 more
core +2 more sources
Optimal Design of Droplet Ejection for PZT Printhead Based on Surrogate Model
Applied Sciences, 2022 Droplet ejection technology is widely used in green and intelligent manufacturing. A stable jetting can be defined as no obvious satellite droplets during the whole ejection process, which is of great importance to ensure the quality and efficiency of ...
Ting Lei, Hong Liu, Cong Ma, Jiang Han
doaj +1 more source
Harmonic balance surrogate-based immunity modeling of a nonlinear analog circuit [PDF]
, 2013 A novel harmonic balance surrogate-based technique to create fast and accurate behavioral models predicting, in the early design stage, the performance of nonlinear analog devices during immunity tests is presented.
Couckuyt, Ivo +6 more
core +2 more sources
A New Cokriging Method for Variable-Fidelity Surrogate Modeling of Aerodynamic Data [PDF]
, 2010 Cokriging is a statistical interpolation method for the enhanced prediction of a less intensively sampled primary variable of interest with assistance of intensively sampled auxiliary variables. In the geostatistics community it is referred to as two- or
Görtz, Stefan +2 more
core +1 more source
IEEE AccessThe machine learning method for surrogate modeling is a keystone in surrogate model-assisted evolutionary algorithms (SAEAs). The current arguably most widely used surrogate modeling methods in SAEAs are Gaussian process and radial basis function.
Yushi Liu +3 more
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Deep Graph Learning-Based Surrogate Model for Inverse Modeling of Fractured Reservoirs
MathematicsInverse modeling can estimate uncertain parameters in subsurface reservoirs and provide reliable numerical models for reservoir development and management. The traditional simulation-based inversion method usually requires numerous numerical simulations,
Xiaopeng Ma +4 more
doaj +1 more source