| 1 |
Cyber-security of centralized, decentralized, and distributed control-detector architectures for nonlinear processes
Chen S, Wu Z, Christofides PD
Chemical Engineering Research & Design, 165, 25, 2021 |
| 2 |
On-line sequential extreme learning machine based on recursive partial least squares
Matias T, Souza F, Araujo R, Goncalves N, Barreto JP
Journal of Process Control, 27, 15, 2015 |
| 3 |
Nonlinear model predictive control for the ALSTOM gasifier
Al Seyab RK, Cao Y
Journal of Process Control, 16(8), 795, 2006 |
| 4 |
Upper bounds for approximation of continuous-time dynamics using delayed outputs and feedforward neural networks
Lavretsky E, Hovakimyan N, Calise AJ
IEEE Transactions on Automatic Control, 48(9), 1606, 2003 |
| 5 |
Colour-appearance modeling using feedforward networks with Bayesian regularization method. Part II: Reverse model
Xin JH, Sijie S, Chung K
Color Research and Application, 27(2), 116, 2002 |
| 6 |
Identification and control of a riser-type FCC unit using neural networks
Alaradi AA, Rohani S
Computers & Chemical Engineering, 26(3), 401, 2002 |
| 7 |
An equation of state for R227ea from density data through a new extended corresponding states-neural network technique
Scalabrin G, Piazza L, Richon D
Fluid Phase Equilibria, 199(1-2), 33, 2002 |
| 8 |
A viscosity equation of state for R134a through a multi-layer feedforward neural network technique
Cristofoli G, Piazza L, Scalabrin G
Fluid Phase Equilibria, 199(1-2), 223, 2002 |
| 9 |
Identification and control of a riser-type FCC unit
Alaradi AA, Rohani S
Canadian Journal of Chemical Engineering, 79(6), 850, 2001 |
| 10 |
Colour-appearance modeling using feedforward networks with Bayesian regularization method - Part I: Forward model
Xin JH, Shao SJ, Chung KFL
Color Research and Application, 25(6), 424, 2000 |
