Computational Intelligence Techniques for Bioprocess Modelling, Supervision and Control (eBook, PDF)
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This research book presents the use of computational intelligence paradigms in bioprocess related tasks namely modeling, supervision, monitoring and control, diagnostic, learning and optimization, with applications to several areas. Aimed at researchers, practitioners and graduate students, it will also serve as a text for advanced courses in chemical engineering, bioinformatics and biotechnology, and for computer scientists interested in bioprocesses. Chapters are self-contained and many of them include applications to real-world problems: - Computational Intelligence Techniques as Tools for ...
This research book presents the use of computational intelligence paradigms in bioprocess related tasks namely modeling, supervision, monitoring and control, diagnostic, learning and optimization, with applications to several areas. Aimed at researchers, practitioners and graduate students, it will also serve as a text for advanced courses in chemical engineering, bioinformatics and biotechnology, and for computer scientists interested in bioprocesses. Chapters are self-contained and many of them include applications to real-world problems: - Computational Intelligence Techniques as Tools for Bioprocess Modelling, Optimization, Supervision and Control; - Software Sensors and their Applications in Bioprocess; - Monitoring of Bioprocesses: Mechanistic and Data-driven Approaches; - Novel Computational Methods for Modeling and Control in Chemical and Biochemical Process Systems; - Computational Intelligence Techniques for Supervision and Diagnosis of Biological Wastewater Treatment Systems; - Multiobjective Genetic Algorithms for the Optimisation of Wastewater Treatment Processes; - Data Reconciliation using Neural Networks for the Determination of KLa; - A Computational Intelligent Based Approach for the Development of a Minimal Defined Medium: Application to Human Interleukin-3 Production by treptomyces lividans 66; - Bioprocess Modelling for Learning Model Predictive Control (L-MPC); - Performance Monitoring and Batch to Batch Control of Biotechnological Processes; - Modelling of Biotechnological Processes - an Approach based on Artificial Neural Networks.
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