| 1 |
Surrogate modeling of phase equilibrium calculations using adaptive sampling
Nentwich C, Engell S
Computers & Chemical Engineering, 126, 204, 2019 |
| 2 |
Evaluating smart sampling for constructing multidimensional surrogate models
Garud SS, Karimi IA, Brownbridge GPE, Kraft M
Computers & Chemical Engineering, 108, 276, 2018 |
| 3 |
Constrained optimization of black-box stochastic systems using a novel feasibility enhanced Kriging-based method
Wang ZL, Ierapetritou M
Computers & Chemical Engineering, 118, 210, 2018 |
| 4 |
A novel feasibility analysis method for black-box processes using a radial basis function adaptive sampling approach
Wang ZL, Ierapetritou M
AIChE Journal, 63(2), 532, 2017 |
| 5 |
Design of computer experiments: A review
Garud SS, Karimi IA, Kraft M
Computers & Chemical Engineering, 106, 71, 2017 |
| 6 |
An adaptive sampling approach for Kriging metamodeling by maximizing expected prediction error
Liu HT, Cai JF, Ong YS
Computers & Chemical Engineering, 106, 171, 2017 |
| 7 |
ADAPTIVE SAMPLING FOR SURROGATE MODELLING WITH ARTIFICIAL NEURAL NETWORK AND ITS APPLICATION IN AN INDUSTRIAL CRACKING FURNACE
Jin YK, Li JL, Du WL, Qian F
Canadian Journal of Chemical Engineering, 94(2), 262, 2016 |
| 8 |
Uncertainty quantification of ion chemistry in lean and stoichiometric homogenous mixtures of methane, oxygen, and argon
Kim D, Rizzi F, Cheng KW, Han J, Bisetti F, Knio OM
Combustion and Flame, 162(7), 2904, 2015 |
| 9 |
Multivehicle coverage control for a nonstationary spatiotemporal field
Sydney N, Paley DA
Automatica, 50(5), 1381, 2014 |
| 10 |
Adaptive sequential sampling for surrogate model generation with artificial neural networks
Eason J, Cremaschi S
Computers & Chemical Engineering, 68, 220, 2014 |
