Results 61 to 70 of about 24,324,331 (382)
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
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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
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A surrogate FRAX model for Nepal [PDF]
Archives of OsteoporosisAbstract Summary A surrogate FRAX® model for Nepal has been constructed using age- and sex-specific hip fracture rates for Indians living in Singapore and age- and sex-specific mortality rates from Nepal. Introduction FRAX
Johansson, H. +5 more
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A PINN Surrogate Modeling Methodology for Steady-State Integrated Thermofluid Systems Modeling
Mathematical and Computational Applications, 2023 Physics-informed neural networks (PINNs) were developed to overcome the limitations associated with the acquisition of large training data sets that are commonly encountered when using purely data-driven machine learning methods.
Kristina Laugksch +2 more
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Reliability Engineering & System SafetyIn the framework of risk assessment, computer codes are increasingly used to understand, model and predict physical phenomena. As these codes can be very time-consuming to run, which severely limit the number of possible simulations, a widely accepted ...
A. Marrel, Bertrand Iooss
semanticscholar +1 more source
Pulsar Signal Adaptive Surrogate Modeling
AerospaceAs the number of spacecraft heading beyond Earth’s orbit increased in recent years, autonomous navigation solutions have become increasingly important. One such solution is pulsar-based navigation.
Tomáš Kašpárek, Peter Chudý
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The Gaussian Process Modeling Module in UQLab [PDF]
Journal of Soft Computing in Civil Engineering, 2018 We introduce the Gaussian process (GP) modeling module developed within the UQLab software framework. The novel design of the GP-module aims at providing seamless integration of GP modeling into any uncertainty quantification workflow, as well as a ...
Christos Lataniotis +2 more
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Quantile-based optimization under uncertainties using adaptive Kriging surrogate models [PDF]
, 2016 Uncertainties are inherent to real-world systems. Taking them into account is crucial in industrial design problems and this might be achieved through reliability-based design optimization (RBDO) techniques.
Bourinet, J. -M. +3 more
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A novel adaptive-weight ensemble surrogate model base on distance and mixture error.
PLoS ONE, 2023 Surrogate models are commonly used as a substitute for the computation-intensive simulations in design optimization. However, building a high-accuracy surrogate model with limited samples remains a challenging task. In this paper, a novel adaptive-weight
Jun Lu, Yudong Fang, Weijian Han
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Surrogate modeling based cognitive decision engine for optimization of WLAN performance [PDF]
, 2017 Due to the rapid growth of wireless networks and the dearth of the electromagnetic spectrum, more interference is imposed to the wireless terminals which constrains their performance. In order to mitigate such performance degradation, this paper proposes
Chemmangat, Krishnan +9 more
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