Results 21 to 30 of about 247,811 (265)

Grid Enabled Surrogate Modeling [PDF]

open access: yes, 2009
The simulation and optimization of complex systems is a very time consuming and computationally intensive task. Therefore, global surrogate modeling methods are often used for the efficient exploration of the design space, as they reduce the number of simulations needed.
Gorissen, Dirk   +3 more
openaire   +3 more sources

Dynamical model of surrogate reactions [PDF]

open access: yesPhysical Review C, 2011
17 pages, 5 ...
Y. Aritomo, S. Chiba, K. Nishio
openaire   +2 more sources

Classical Surrogates for Quantum Learning Models

open access: yesPhysical Review Letters, 2023
The advent of noisy intermediate-scale quantum computers has put the search for possible applications to the forefront of quantum information science. One area where hopes for an advantage through near-term quantum computers are high is quantum machine learning, where variational quantum learning models based on parametrized quantum circuits are ...
Franz J. Schreiber   +2 more
openaire   +3 more sources

Kernel Methods for Surrogate Modeling

open access: yesCoRR, 2019
This chapter deals with kernel methods as a special class of techniques for surrogate modeling. Kernel methods have proven to be efficient in machine learning, pattern recognition and signal analysis due to their flexibility, excellent experimental performance and elegant functional analytic background.
Santin G., Haasdonk B.
openaire   +2 more sources

Response surface methodology using a prior knowledge and its application to pin fin heat sink design

open access: yesNihon Kikai Gakkai ronbunshu, 2019
Large number of simulations or experiments is needed for optimization and uncertainty quantification of a mechanical system. Therefore, if simulations or experiments are numerically expensive and time consuming, it is difficult to execute optimization ...
Kazuo MUTO, Makoto ONODERA
doaj   +1 more source

GTApprox: Surrogate modeling for industrial design [PDF]

open access: yesAdvances in Engineering Software, 2016
31 pages, 11 ...
Mikhail Belyaev   +6 more
openaire   +2 more sources

Hierarchical Surrogate-Assisted Evolutionary Algorithm for Integrated Multi-Objective Optimization of Well Placement and Hydraulic Fracture Parameters in Unconventional Shale Gas Reservoir

open access: yesEnergies, 2022
Integrated optimization of well placement and hydraulic fracture parameters in naturally fractured shale gas reservoirs is of significance to enhance unconventional hydrocarbon energy resources in the oil and gas industry.
Jun Zhou   +3 more
doaj   +1 more source

Multiscale topology optimisation with nonparametric microstructures using three-dimensional convolutional neural network (3D-CNN) models

open access: yesVirtual and Physical Prototyping, 2021
Additive manufacturing enables the fabrication of parts with complex geometries, thereby opening up the design space from part scale to microarchitecture scale.
Guo Yilin   +2 more
doaj   +1 more source

Comparison of a Response Surface Method and Artificial Neural Network in Predicting the Aerodynamic Performance of a Wind Turbine Airfoil and Its Optimization

open access: yesApplied Sciences, 2020
To find the optimal design for an engineering object, thousands of (or even more) simulations should be implemented to obtain the outcome data for the variously designed objects.
Sahuck Oh
doaj   +1 more source

On the use of gradients in Kriging surrogate models [PDF]

open access: yesProceedings of the Winter Simulation Conference 2014, 2014
The use of Kriging surrogate models has become popular in approximating computation-intensive deterministic computer models. In this work, the effect of enhancing Kriging surrogate models with a (partial) set of gradients is investigated. While, intuitively, gradient information is useful to enhance prediction accuracy, another motivation behind this ...
Selvakumar Ulaganathan   +4 more
openaire   +2 more sources

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