| 1 - 11 |
A novel dynamic PCA algorithm for dynamic data modeling and process monitoring
Dong YN, Qin SJ |
| 12 - 22 |
Dynamic concurrent kernel CCA for strip-thickness relevant fault diagnosis of continuous annealing processes
Liu Q, Zhu QQ, Qin SJ, Chai TY |
| 23 - 34 |
Semi-supervised online soft sensor maintenance experiences in the chemical industry
Lu B, Chiang L |
| 35 - 43 |
Statistical process monitoring as a big data analytics tool for smart manufacturing
He QP, Wang J |
| 44 - 55 |
A scalable design of experiments framework for optimal sensor placement
Yu J, Zavala VM, Anitescu M |
| 56 - 68 |
Data-driven adaptive multiple model system utilizing growing self-organizing maps
Lu B, Stuber J, Edgar TF |
| 69 - 82 |
Comparative study on monitoring schemes for non-Gaussian distributed processes
Li G, Qin SJ |
| 83 - 93 |
An improved variable selection method for support vector regression in NIR spectral modeling
Xu S, Lu B, Baldea M, Edgar TF, Nixon M |
| 94 - 111 |
Robust probabilistic principal component analysis based process modeling: Dealing with simultaneous contamination of both input and output data
Sadeghian A, Wu O, Huang B |
| 112 - 128 |
Real-time fault detection and diagnosis using sparse principal component analysis
Gajjar S, Kulahci M, Palazoglu A |
| 129 - 140 |
Novel sparse LSSVR models in primal weight space for robust system identification with outliers
Santos JDA, Barreto GA |
| 141 - 159 |
Big Data Approximating Control (BDAC)-A new model-free estimation and control paradigm based on pattern matching and approximation
Stanley GM |
| 160 - 175 |
Data mining and clustering in chemical process databases for monitoring and knowledge discovery
Thomas MC, Zhu WB, Romagnoli JA |
| 176 - 196 |
Multilevel MVU models with localized construction for monitoring processes with large scale data
Wei CH, Chen JH, Song ZH |
| 197 - 205 |
A geometric method for batch data visualization, process monitoring and fault detection
Wang R, Edgar TF, Baldea M, Nixon M, Wojsznis W, Dunia R |
| III - III |
Special issue on big data: Data science for process control and operations Preface
Qin SJ |
