| 1 |
Technology transfer of a monitoring system to predict product concentration and purity of biopharmaceuticals in real-time during chromatographic separation
Christler A, Scharl T, Sauer DG, Koppl J, Tscheliessnig A, Toy C, Melcher M, Jungbauer A, Durauer A
Biotechnology and Bioengineering, 118(10), 3941, 2021 |
| 2 |
Soft sensor development based on improved just-in-time learning and relevant vector machine for batch processes
Wang JL, Qiu KP, Guo YQ, Wang RT, Zhou XJ
Canadian Journal of Chemical Engineering, 99(1), 334, 2021 |
| 3 |
Adaptive Soft Sensor Modeling Method for Time-varying and Multi-Dimensional Chemical Processes
Li LH, Dai YS
Journal of Chemical Engineering of Japan, 54(2), 63, 2021 |
| 4 |
Bayesian network for dynamic variable structure learning and transfer modeling of probabilistic soft sensor
Zeng L, Ge ZQ
Journal of Process Control, 100, 20, 2021 |
| 5 |
Data-driven techniques for fault detection in anaerobic digestion process
Kazemi P, Bengoa C, Steyer JP, Giralt J
Process Safety and Environmental Protection, 146, 905, 2021 |
| 6 |
A robust soft sensor to monitor 1,3-propanediol fermentation process byClostridium butyricumbased on artificial neural network
Zhang AH, Zhu KY, Zhuang XY, Liao LX, Huang SY, Yao CY, Fang BS
Biotechnology and Bioengineering, 117(11), 3345, 2020 |
| 7 |
Biomass soft sensor for aPichia pastorisfed-batch process based on phase detection and hybrid modeling
Brunner V, Siegl M, Geier D, Becker T
Biotechnology and Bioengineering, 117(9), 2749, 2020 |
| 8 |
Mixture robust L1 probabilistic principal component regression and soft sensor application
Zhu PB, Yang XQ, Zhang H
Canadian Journal of Chemical Engineering, 98(8), 1741, 2020 |
| 9 |
Linking process variables to residence time distribution in a hybrid flowsheet model for continuous direct compression
Galbraith SC, Park S, Huang Z, Liu H, Meyer RF, Metzger M, Flamm MH, Hurley S, Yoon S
Chemical Engineering Research & Design, 153, 85, 2020 |
| 10 |
Separation Units 4.0-Trenntechnik in der chemischen Industrie auf dem Weg in die digitale Zukunft. Eindrucke und erste Ergebnisse vom Tutzing-Symposion 2019
Bart HJ, Grunewald M, Repke JU, Scholl S
Chemie Ingenieur Technik, 92(7), 807, 2020 |
