Results 11 to 20 of about 247,811 (265)
ArraySurrogate-assisted evolutionary algorithms (SAEAs) are widely used to solve expensive optimization problems where evaluating candidate solutions is computationally intensive. To reduce this cost, SAEAs employ surrogate models—machine learning models that
Yuki Hanawa +2 more
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A surrogate FRAX model for Pakistan [PDF]
Archives of Osteoporosis, 2021 Abstract Summary A surrogate FRAX® model for Pakistan has been constructed using age-specific hip fracture rates for Indians living in Singapore and age-specific mortality rates from Pakistan.
Naureen, G. +11 more
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Combined surrogate model for stress prediction of spherical bulkhead with openings
Zhongguo Jianchuan Yanjiu, 2022 ObjectiveA spherical bulkhead with openings has many structural parameters, and it is time-consuming and laborious to directly use the finite element method to carry out parameter research.
Tianyi CHEN +3 more
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Efficient surrogate modeling methods for large-scale Earth system models based on machine-learning techniques [PDF]
Geoscientific Model Development, 2019 Improving predictive understanding of Earth system variability and change requires data–model integration. Efficient data–model integration for complex models requires surrogate modeling to reduce model evaluation time. However, building a surrogate of a
D. Lu, D. Ricciuto
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Ensemble-Assisted Multi-Objective Optimization Algorithm Combining Feature Perturbation and Allocation Strategy [PDF]
Jisuanji gongcheng, 2022 A surrogate model can use its approximate prediction to replace the real evaluation of an algorithm when applied to the multi-objective optimization problem, which greatly reduces the number of real fitness evaluations required by the multi-objective ...
LIU Ziyi, WANG Yujia, SUN Fulu, JIA Xin, NIE Fangxin
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The Creation of Surrogate Models for Fast Estimation of Complex Model Outcomes. [PDF]
PLoS ONE, 2016 A surrogate model is a black box model that reproduces the output of another more complex model at a single time point. This is to be distinguished from the method of surrogate data, used in time series.
W Andrew Pruett, Robert L Hester
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Energy and AI, 2021 A data-driven surrogate model is proposed for a 64-cell air-cooled condenser system at a power plant. The surrogate model was developed using thermofluid simulation data from an existing detailed 1-D thermofluid network simulation model.
Rashid A. Haffejee, Ryno Laubscher
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Physics-based surrogate model for reinforced concrete corrosion simulation
Results in Engineering, 2022 Computational models have been used in conjunction with field data, such as in reinforcement concrete corrosion monitoring. It typically involves evaluating the physical model of the corrosion process.
Syifaul Huzni +3 more
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Evaluation of POD based surrogate models of fields resulting from nonlinear FEM simulations
Advanced Modeling and Simulation in Engineering Sciences, 2021 Surrogate modelling is a powerful tool to replace computationally expensive nonlinear numerical simulations, with fast representations thereof, for inverse analysis, model-based control or optimization.
Boukje M. de Gooijer +3 more
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Surrogate Leadership Model for Digital Organizational Systems [PDF]
Business Ethics and Leadership, 2020 The increase of investigations regarding digital systems for the social structure mapping leads to dynamizing previously rigidly recorded processes or deliberately ignored ones.
Olena Skrynnyk
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