A screening-based gradient-enhanced Kriging modeling method for high-dimensional problems

DOI10.1016/j.apm.2018.11.048zbMath1470.74069OpenAlexW2905397490WikidataQ128764380 ScholiaQ128764380MaRDI QIDQ2310508

Yanyan Li

Publication date: 6 April 2020

Published in: Applied Mathematical Modelling (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.apm.2018.11.048

zbMATH Keywords

design optimizationsurrogate modelfeature selection techniqueoptimal airfoil shapepartial gradient set

Mathematics Subject Classification ID

Optimization of other properties in solid mechanics (74P10) Flow control and optimization for compressible fluids and gas dynamics (76N25) Numerical and other methods in solid mechanics (74S99)

Related Items

Adaptive kriging-assisted optimization of low-thrust many-revolution transfers to geostationary Earth orbit ⋮ Sliced Gradient-Enhanced Kriging for High-Dimensional Function Approximation ⋮ Surrogate modeling for high dimensional uncertainty propagation via deep kernel polynomial chaos expansion ⋮ A novel sampling method for adaptive gradient-enhanced kriging ⋮ Model-data-driven constitutive responses: application to a multiscale computational framework ⋮ A combined radial basis function and adaptive sequential sampling method for structural reliability analysis ⋮ Optimization of expensive black-box problems via gradient-enhanced Kriging

Uses Software

• DACE
• EGO
• SU2
• JADE

Cites Work

• Survey of modeling and optimization strategies to solve high-dimensional design problems with computationally-expensive black-box functions
• Is mutual information adequate for feature selection in regression?
• High dimensional model representation for stochastic finite element analysis
• Aerodynamic design via control theory
• Efficient global optimization of expensive black-box functions
• Design and analysis of computer experiments. With comments and a rejoinder by the authors
• A derivative based surrogate model for approximating and optimizing the output of an expensive computer simulation
• Analysis methods for computer experiments: how to assess and what counts?
• A taxonomy of global optimization methods based on response surfaces
• Multivariate plug-in bandwidth selection
• A surrogate based multi-fidelity approach for robust design optimization
• High dimensional kriging metamodelling utilising gradient information
• A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code
• Bayesian Design and Analysis of Computer Experiments: Use of Derivatives in Surface Prediction
• Remarks on Some Nonparametric Estimates of a Density Function
• 10.1162/153244303322753616
• Predicting the output from a complex computer code when fast approximations are available
• On the Maximum Likelihood Training of Gradient-Enhanced Spatial Gaussian Processes
• On Estimation of a Probability Density Function and Mode
• An introduction to the adjoint approach to design

This page was built for publication: A screening-based gradient-enhanced Kriging modeling method for high-dimensional problems