Blar i NTNU Open på forfatter "del Rio-Chanona, Ehecatl Antonio"
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Dynamic modeling and optimization of sustainable algal production with uncertainty using multivariate Gaussian processes
Bradford, Eric; Schweidtmann, Artur M.; Zhang, Dongda; Jing, Keju; del Rio-Chanona, Ehecatl Antonio (Journal article; Peer reviewed, 2018)Dynamic modeling is an important tool to gain better understanding of complex bioprocesses and to determine optimal operating conditions for process control. Currently, two modeling methodologies have been applied to ... -
Reinforcement Learning for Batch Bioprocess Optimization
Petsagkourakis, Panagiotis; Sandoval, Ilya Orson; Bradford, Eric; Zhang, Dongda; del Rio-Chanona, Ehecatl Antonio (Peer reviewed; Journal article, 2020)Bioprocesses have received a lot of attention to produce clean and sustainable alternatives to fossil-based materials. However, they are generally difficult to optimize due to their unsteady-state operation modes and ... -
Reinforcement Learning for Batch-to-Batch Bioprocess Optimisation
Petsagkourakis, Panagiotis; Sandoval, Ilya Orson; Bradford, Eric; Zhang, Dongda; del Rio-Chanona, Ehecatl Antonio (Chapter, 2019)Bioprocesses have received great attention from the scientific community as an alternative to fossil-based products by microorganisms-synthesised counterparts. However, bioprocesses are generally operated at unsteady-state ... -
Review of advanced physical and data‐driven models for dynamic bioprocess simulation: Case study of algae–bacteria consortium wastewater treatment
del Rio-Chanona, Ehecatl Antonio; Cong, Xiaoying; Bradford, Eric; Zhang, Dongda; Jing, Keju (Peer reviewed; Journal article, 2019)Microorganism production and remediation processes are of critical importance to the next generation of sustainable industries. Undertaking mathematical treatment of dynamic biosystems operating at any spatial or temporal ...