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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| Auteurs principaux: | , , |
|---|---|
| 格式: | Livre numérique |
| 語言: | Anglais |
| 出版: |
Berlin, Heidelberg :
Springer Berlin Heidelberg
[20..].
Cham : Springer Nature |
| 版: | 1st ed. 2006. |
| 叢編: | Studies in Computational Intelligence
15 |
| 在線閱讀: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| 提示: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Modelling and optimization of biotechnological processes, artificial intelligence approaches, Lei Zhi Chen, Sing Kiong Nguang, Xiao Dong Chen, Berlin, Springer, 2006, 1 vol. (viii-123 p)., Studies in computational intelligence, 3-540-30634-X • Modelling and Optimization of Biotechnological Processes, Texte imprimé, 9783642067921 • Modelling and Optimization of Biotechnological Processes, Texte imprimé, 9783540818281 • Modelling and optimization of biotechnological processes, artificial intelligence approaches, Lei Zhi Chen, Sing Kiong Nguang, Xiao Dong Chen, Berlin, Springer, 2006, 1 vol. (viii-123 p)., Studies in computational intelligence, 3-540-30634-X |
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| 100 | 1 | |a Chen, Lei Zhi. | |
| 245 | 1 | 0 | |a Modelling and optimization of biotechnological processes : |b Artificial Intelligence Approaches |c by Lei Zhi Chen, Sing Kiong Nguang, Xiao Dong Chen. |
| 250 | |a 1st ed. 2006. | ||
| 260 | |a Berlin, Heidelberg : |b Springer Berlin Heidelberg. | ||
| 260 | |a Cham : |b Springer Nature, |c [20..]. | ||
| 490 | 0 | |a Studies in Computational Intelligence |v 15 |x 1860-9503 | |
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 505 | 1 | |a Optimization of Fed-batch Culture of Hybridoma Cells using Genetic Algorithms On-line Identification and Optimization of Feed Rate Profiles for Fed-batch Culture of Hybridoma Cells On-line Softsensor Development for Biomass Measurements using Dynamic Neural Networks Optimization of Fed-batch Fermentation Processes using Genetic Algorithms based on Cascade Dynamic Neural Network Models Experimental Validation of Cascade Recurrent Neural Network Models Designing and Implementing Optimal Control of Fed-batch Fermentation Processes Conclusions | |
| 506 | |a Accès en ligne pour les établissements français bénéficiaires des licences nationales | ||
| 506 | |a Accès soumis à abonnement pour tout autre établissement | ||
| 506 | |a Conditions particulières de réutilisation pour les bénéficiaires des licences nationales. https://www.licencesnationales.fr/springer-nature-ebooks-contrat-licence-ln-2017 | ||
| 520 | |a 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 | ||
| 700 | 1 | |a Chen, Xiaodong. |4 aut | |
| 700 | 1 | |a Nguang, Sing Kiong. |4 aut | |
| 776 | 0 | |0 105998346 |t Modelling and optimization of biotechnological processes |o artificial intelligence approaches |f Lei Zhi Chen, Sing Kiong Nguang, Xiao Dong Chen |c Berlin |n Springer |d 2006 |p 1 vol. (viii-123 p). |s Studies in computational intelligence |z 3-540-30634-X | |
| 776 | 0 | |t Modelling and Optimization of Biotechnological Processes |b Texte imprimé |z 9783642067921 | |
| 776 | 0 | |t Modelling and Optimization of Biotechnological Processes |b Texte imprimé |z 9783540818281 | |
| 776 | 0 | |0 105998346 |t Modelling and optimization of biotechnological processes |o artificial intelligence approaches |f Lei Zhi Chen, Sing Kiong Nguang, Xiao Dong Chen |c Berlin |n Springer |d 2006 |p 1 vol. (viii-123 p). |s Studies in computational intelligence |z 3-540-30634-X | |
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