Cikkek nyilvánosan hozzáférhető megbízással - Lianfang CaiTovábbi információ
Sehol sem hozzáférhető: 6
A new fault detection method for non-Gaussian process based on robust independent component analysis
L Cai, X Tian
Process Safety and Environmental Protection 92 (6), 645-658, 2014
Megbízások: National Natural Science Foundation of China
Process fault detection based on dynamic kernel slow feature analysis
N Zhang, X Tian, L Cai, X Deng
Computers & Electrical Engineering 41, 9-17, 2015
Megbízások: National Natural Science Foundation of China
A kernel time structure independent component analysis method for nonlinear process monitoring
L Cai, X Tian, N Zhang
Chinese Journal of Chemical Engineering 22 (11-12), 1243-1253, 2014
Megbízások: National Natural Science Foundation of China
A multi-index control performance assessment method based on historical prediction error covariance
L Shang, X Tian, L Cai
IFAC-PapersOnLine 50 (1), 13892-13897, 2017
Megbízások: National Natural Science Foundation of China
A new soft sensor method for dynamic processes based on dynamic orthogonal forward regression
R Hongmei, T Xuemin, C Lianfang
The 27th Chinese Control and Decision Conference (2015 CCDC), 536-541, 2015
Megbízások: National Natural Science Foundation of China
FIM-based pairwise selection for active learning on imbalanced datasets
L Chen, X Tian, L Cai
2015 IEEE International Conference on Systems, Man, and Cybernetics, 1876-1881, 2015
Megbízások: National Natural Science Foundation of China
Valahol hozzáférhető: 10
Monitoring nonlinear and non-Gaussian processes using Gaussian mixture model-based weighted kernel independent component analysis
L Cai, X Tian, S Chen
IEEE transactions on neural networks and learning systems 28 (1), 122-135, 2015
Megbízások: National Natural Science Foundation of China
Wide-Area Monitoring of Power Systems Using Principal Component Analysis and -Nearest Neighbor Analysis
L Cai, NF Thornhill, S Kuenzel, BC Pal
IEEE Transactions on Power Systems 33 (5), 4913-4923, 2018
Megbízások: UK Engineering and Physical Sciences Research Council
Real-Time Detection of Power System Disturbances Based on -Nearest Neighbor Analysis
L Cai, NF Thornhill, S Kuenzel, BC Pal
IEEE Access 5, 5631-5639, 2017
Megbízások: UK Engineering and Physical Sciences Research Council
Noise-resistant joint diagonalization independent component analysis based process fault detection
X Tian, L Cai, S Chen
Neurocomputing 149, 652-666, 2015
Megbízások: National Natural Science Foundation of China
Nonlinear process fault diagnosis using kernel slow feature discriminant analysis
H Zhang, X Tian, L Cai
IFAC-PapersOnLine 48 (21), 607-612, 2015
Megbízások: National Natural Science Foundation of China
Multivariate detection of power system disturbances based on fourth order moment and singular value decomposition
L Cai, NF Thornhill, BC Pal
IEEE Transactions on Power Systems 32 (6), 4289-4297, 2017
Megbízások: UK Engineering and Physical Sciences Research Council
A local and global statistics pattern analysis method and its application to process fault identification
H Zhang, X Tian, X Deng, L Cai
Chinese Journal of Chemical Engineering 23 (11), 1782-1792, 2015
Megbízások: National Natural Science Foundation of China
A test model of a power grid with battery energy storage and wide-area monitoring
L Cai, NF Thornhill, S Kuenzel, BC Pal
IEEE Transactions on Power Systems 34 (1), 380-390, 2018
Megbízások: UK Engineering and Physical Sciences Research Council
Process fault detection method based on time structure independent component analysis and one-class support vector machine
L Cai, X Tian, H Zhang
IFAC-PapersOnLine 48 (21), 1198-1203, 2015
Megbízások: National Natural Science Foundation of China
A semi-empirical state of health estimation method for batteries of electric vehicles operating in varying real-world conditions
L Cai, M Holdstock, MV Morganti, S Ayyapureddi, A McGordon
IEEE Access, 2024
Megbízások: UK Research & Innovation
A publikációs és a finanszírozási adatokat számítógépes program határozza meg, automatikusan.