Abstract
Four different modelling techniques are considered for the Escherichia coli fermentation process. These are Multiple Linear Regression (MLR), Principal Component Regression (PCR), Non-linear Auto-Regressive Moving Average with eXogeneous inputs (NARMAX) and Artificial Neural Networks (ANNs). The models use industrial on-line data from the process as inputs in order to forecast the concentrations of biomass and recombinant protein, normally only available from off-line laboratory analysis. The models* performances are compared by prediction accuracy and graphical fit using results obtained from a common set of fermentation data.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
