8 citations · 9 across the 5 of their papers we have counts for
5 papers
Cubature-based uncertainty estimation for nonlinear regression models
Martin Bubel, Jochen Schmid, Maximilian Carmesin +3
Calibrating model parameters to measured data by minimizing loss functions is an important step in obtaining realistic predictions from model-based approaches, e.g., for process op…
Why fixing alpha in the NRTL model might be a bad idea -- Identifiability analysis of a binary Vapor-Liquid equilibrium
Volodymyr Kozachynskyi, Christian Hoffmann, Erik Esche
New vapor-liquid equilibrium (VLE) data are continuously being measured and new parameter values, e.g., for the nonrandom two-liquid (NRTL) model are estimated and published. The p…
Sequential optimal experimental design for vapor-liquid equilibrium modeling
Martin Bubel, Jochen Schmid, Volodymyr Kozachynskyi +2
We propose a general methodology of sequential locally optimal design of experiments for explicit or implicit nonlinear models, as they abound in chemical engineering and, in parti…
Adaptive Sampling of Dynamic Systems for Generation of Fast and Accurate Surrogate Models
Torben Talis, Joris Weigert, Erik Esche +1
For economic nonlinear model predictive control and dynamic real-time optimization fast and accurate models are necessary. Consequently, the use of dynamic surrogate models to mimi…
Semi-supervised Learning for Data-driven Soft-sensing of Biological and Chemical Processes
Erik Esche, Torben Talis, Joris Weigert +4
Continuously operated (bio-)chemical processes increasingly suffer from external disturbances, such as feed fluctuations or changes in market conditions. Product quality often hing…