| 1 |
Deep learning-based initial guess for minimum energy path calculations
Park HS, Lee SW, Kim JH
Korean Journal of Chemical Engineering, 38(2), 406, 2021 |
| 2 |
Development of augmented virtual reality-based operator training system for accident prevention in a refinery
Ko CJ, Lee HD, Lim YS, Lee WB
Korean Journal of Chemical Engineering, 38(8), 1566, 2021 |
| 3 |
Data-driven fault detection for chemical processes using autoencoder with data augmentation
Lee HD, Kim CS, Jeong DH, Lee JM
Korean Journal of Chemical Engineering, 38(12), 2406, 2021 |
| 4 |
Wind turbine fault diagnosis based on transfer learning and convolutional autoencoder with small-scale data
Li YT, Jiang WB, Zhang GY, Shu LJ
Renewable Energy, 171, 103, 2021 |
| 5 |
Deep learning technique for process fault detection and diagnosis in the presence of incomplete data
Guo C, Hu WK, Yang F, Huang DX
Chinese Journal of Chemical Engineering, 28(9), 2358, 2020 |
| 6 |
Output-relevant Variational autoencoder for Just-in-time soft sensor modeling with missing data
Guo F, Bai WT, Huang B
Journal of Process Control, 92, 90, 2020 |
| 7 |
System-wide anomaly detection in wind turbines using deep autoencoders
Renstrom N, Bangalore P, Highcock E
Renewable Energy, 157, 647, 2020 |
| 8 |
Intelligent simultaneous fault diagnosis for solid oxide fuel cell system based on deep learning
Zhang ZH, Li SH, Xiao YW, Yang YP
Applied Energy, 233, 930, 2019 |
| 9 |
Parallel neural networks for improved nonlinear principal component analysis
Heo S, Lee JH
Computers & Chemical Engineering, 127, 1, 2019 |
| 10 |
Gaussian feature learning based on variational autoencoder for improving nonlinear process monitoring
Zhang ZH, Jiang T, Zhan CJ, Yang YP
Journal of Process Control, 75, 136, 2019 |
