Selection of surrogate modeling techniques for surface approximation and surrogate-based optimization
Published 2021 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Selection of surrogate modeling techniques for surface approximation and surrogate-based optimization
Authors
Keywords
Surrogate model, Surface approximation, Surrogate-based optimization, Random forests, Multivariate adaptive regression splines, Gaussian process regression
Journal
CHEMICAL ENGINEERING RESEARCH & DESIGN
Volume 170, Issue -, Pages 76-89
Publisher
Elsevier BV
Online
2021-04-04
DOI
10.1016/j.cherd.2021.03.028
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Prediction of Human Induced Pluripotent Stem Cell Cardiac Differentiation Outcome by Multifactorial Process Modeling
- (2020) Bianca Williams et al. Frontiers in Bioengineering and Biotechnology
- Multi-objective Optimization of Sulfur Recovery Units Using a Detailed Reaction Mechanism to Reduce Energy Consumption and Destruct Feed Contaminants
- (2019) Ramees K. Rahman et al. COMPUTERS & CHEMICAL ENGINEERING
- Integrated process design, scheduling, and control using multiparametric programming
- (2019) Baris Burnak et al. COMPUTERS & CHEMICAL ENGINEERING
- Advances in surrogate based modeling, feasibility analysis, and optimization: A review
- (2018) Atharv Bhosekar et al. COMPUTERS & CHEMICAL ENGINEERING
- Support vector regression modelling and optimization of energy consumption in carbon fiber production line
- (2018) Gelayol Golkarnarenji et al. COMPUTERS & CHEMICAL ENGINEERING
- Fault detection of broken rotor bar in LS-PMSM using random forests
- (2018) Juan C. Quiroz et al. MEASUREMENT
- Automatic selection for general surrogate models
- (2018) Malek Ben Salem et al. STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
- A Data-Driven Design for Fault Detection of Wind Turbines Using Random Forests and XGboost
- (2018) Dahai Zhang et al. IEEE Access
- Concurrent surrogate model selection (COSMOS): optimizing model type, kernel function, and hyper-parameters
- (2017) Ali Mehmani et al. STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
- Statistical Metamodeling and Sequential Design of Computer Experiments to Model Glyco-Altered Gating of Sodium Channels in Cardiac Myocytes
- (2016) Dongping Du et al. IEEE Journal of Biomedical and Health Informatics
- Artificial intelligence metamodel comparison and application to wind turbine airfoil uncertainty analysis
- (2016) Yaping Ju et al. Advances in Mechanical Engineering
- Surrogate modeling of multifidelity data for large samples
- (2015) E. V. Burnaev et al. JOURNAL OF COMMUNICATIONS TECHNOLOGY AND ELECTRONICS
- Learning surrogate models for simulation-based optimization
- (2014) Alison Cozad et al. AICHE JOURNAL
- An evaluation of adaptive surrogate modeling based optimization with two benchmark problems
- (2014) Chen Wang et al. ENVIRONMENTAL MODELLING & SOFTWARE
- Comparison of surrogate models with different methods in groundwater remediation process
- (2014) Jiannan Luo et al. Journal of Earth System Science
- A comparison of eight metamodeling techniques for the simulation of N2O fluxes and N leaching from corn crops
- (2011) Nathalie Villa-Vialaneix et al. ENVIRONMENTAL MODELLING & SOFTWARE
- Constructing Sobol Sequences with Better Two-Dimensional Projections
- (2008) Stephen Joe et al. SIAM JOURNAL ON SCIENTIFIC COMPUTING
Publish scientific posters with Peeref
Peeref publishes scientific posters from all research disciplines. Our Diamond Open Access policy means free access to content and no publication fees for authors.
Learn MoreAsk a Question. Answer a Question.
Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.
Get Started