Modelling and Optimization of Biotechnological Processes Artificial Intelligence Approaches

This book presents logical approaches to monitoring, modelling and optimization of fed-batch fermentation processes based on artificial intelligence methods, in particular, neural networks and genetic algorithms. Both computer simulation and experimental validation are demonstrated in this book. The...

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Bibliographic Details
Main Authors: Chen, Lei Zhi, Nguang, Sing Kiong (Author), Chen, Xiao Dong (Author)
Format: eBook
Language:English
Published: Berlin, Heidelberg Springer Berlin Heidelberg 2006, 2006
Edition:1st ed. 2006
Series:Studies in Computational Intelligence
Subjects:
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
Description
Summary:This book presents logical approaches to monitoring, modelling and optimization of fed-batch fermentation processes based on artificial intelligence methods, in particular, neural networks and genetic algorithms. Both computer simulation and experimental validation are demonstrated in this book. The approaches proposed in this book can be readily adopted for different processes and control schemes to achieve maximum productivity with minimum development and production costs. These approaches can eliminate the difficulties of having to specify completely the structures and parameters of highly nonlinear bioprocess models. The book begins with a historical introduction to the field of bioprocess control based on artificial intelligence approaches, followed by two chapters covering the optimization of fed-batch culture using genetic algorithms. Online biomass soft-sensors are constructed in Chapter 4 using recurrent neural networks. The bioprocess is then modelled in Chapter 5 by cascading two soft-sensor neural networks. Optimization and validation of the final product are detailed in Chapters 6 and 7. The general conclusions are drawn in Chapter 8
Physical Description:VIII, 123 p online resource
ISBN:9783540324935