| 1 |
Multiphase batch process monitoring based on higher-order cumulant analysis
Chang P, Qiao JF, Lu RW, Zhang XY
Canadian Journal of Chemical Engineering, 98(2), 513, 2020 |
| 2 |
A GRU Network-Based Approach for Steam Drum Water Level Predictions
Ma Y, Li HG
Journal of Chemical Engineering of Japan, 53(5), 198, 2020 |
| 3 |
Online reduced kernel GLRT technique for improved fault detection in photovoltaic systems
Fezai R, Mansouri M, Trabelsi M, Hajji M, Nounou H, Nounou M
Energy, 179, 1133, 2019 |
| 4 |
Total plant performance evaluation based on big data: Visualization analysis of TE process
Li MY, Du WL, Qian F, Zhong WM
Chinese Journal of Chemical Engineering, 26(8), 1736, 2018 |
| 5 |
Combination of KPCA and causality analysis for root cause diagnosis of industrial process fault
Gharahbagheri H, Imtiaz S, Khan F
Canadian Journal of Chemical Engineering, 95(8), 1497, 2017 |
| 6 |
Nonlinear Gaussian Belief Network based fault diagnosis for industrial processes
Yu HY, Khan F, Garaniya V
Journal of Process Control, 35, 178, 2015 |
| 7 |
Condition Monitoring of Combustion Processes Through Flame Imaging and Kernel Principal Component Analysis
Sun D, Lu G, Zhou H, Yan Y
Combustion Science and Technology, 185(9), 1400, 2013 |
| 8 |
The optimization of the kind and parameters of kernel function in KPCA for process monitoring
Jia MX, Xu HY, Liu XF, Wang N
Computers & Chemical Engineering, 46, 94, 2012 |
| 9 |
Learning a data-dependent kernel function for KPCA-based nonlinear process monitoring
Shao JD, Rong G, Lee JM
Chemical Engineering Research & Design, 87(11A), 1471, 2009 |
| 10 |
Enhanced statistical analysis of nonlinear processes using KPCA, KICA and SVM
Zhang YW
Chemical Engineering Science, 64(5), 801, 2009 |
