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Machine learning in coastal bridge hydrodynamics: a state-of-the-art review
Coastal bridges are vulnerable to complicated hydrodynamics induced by hostile natural
hazards, relevant research is thus required to ensure the safe operation of these critical …
hazards, relevant research is thus required to ensure the safe operation of these critical …
A radial basis function-based multi-fidelity surrogate model: exploring correlation between high-fidelity and low-fidelity models
In computational simulation, a high-fidelity (HF) model is generally more accurate than a low-
fidelity (LF) model, while the latter is generally more computationally efficient than the …
fidelity (LF) model, while the latter is generally more computationally efficient than the …
Ensemble of surrogates in black-box-type engineering optimization: Recent advances and applications
Due to its high efficiency, surrogate models have been extensively used in black-box-type
engineering optimization problems. However, due to the nature of black-box functions, it is …
engineering optimization problems. However, due to the nature of black-box functions, it is …
Impeller shape-optimization of stirred-tank reactor: CFD and fluid structure interaction analyses
Mixing is an important operation in the chemical industry. The present numerical study,
validated by experimental data, offers a computational framework for minimizing the stirred …
validated by experimental data, offers a computational framework for minimizing the stirred …
Identifying the release history of a groundwater contaminant source based on an ensemble surrogate model
Z **ng, R Qu, Y Zhao, Q Fu, Y Ji, W Lu - Journal of Hydrology, 2019 - Elsevier
In identifying groundwater contaminant sources, given that the simulation model is
computationally inefficient, an ensemble surrogate model is proposed to improve the …
computationally inefficient, an ensemble surrogate model is proposed to improve the …
An adaptive hybrid surrogate model
The determination of complex underlying relationships between system parameters from
simulated and/or recorded data requires advanced interpolating functions, also known as …
simulated and/or recorded data requires advanced interpolating functions, also known as …
Optimization investigation on configuration parameters of spiral-wound heat exchanger using Genetic Aggregation response surface and Multi-Objective Genetic …
S Wang, G Jian, J **ao, J Wen, Z Zhang - Applied Thermal Engineering, 2017 - Elsevier
Based on the method combining Genetic Aggregation response surface and Multi-Objective
Genetic Algorithm, the effects of configuration parameters of spiral-wound heat exchanger …
Genetic Algorithm, the effects of configuration parameters of spiral-wound heat exchanger …
Ensemble learning based hierarchical surrogate model for multi-fidelity information fusion
Recently, multi-fidelity information fusion based surrogate modeling methods have made
great progress in the engineering design and optimization tasks. Two main issues in this …
great progress in the engineering design and optimization tasks. Two main issues in this …
An advanced and robust ensemble surrogate model: extended adaptive hybrid functions
Hybrid or ensemble surrogate models developed in recent years have shown a better
accuracy compared to individual surrogate models. However, it is still challenging for hybrid …
accuracy compared to individual surrogate models. However, it is still challenging for hybrid …
[PDF][PDF] SURROGATES Toolbox User's Guide, Version 3.0
FAC Viana - Gainesville, FL, USA, 2011 - tatmou.com
I am deeply grateful to Dr. Raphael Haftka for his guidance during the development of this
toolbox and for his valuable comments on the documentation. I thank Dr. Tushar Goel for his …
toolbox and for his valuable comments on the documentation. I thank Dr. Tushar Goel for his …