| Artificial intelligence and the supervision of bioprocesses (real-time knowledge-based systems and neural networks). | |
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MedLine Citation:
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PMID: 8460575 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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The ability to supervise and control a highly non-linear and time variant bioprocess is of considerable importance to the biotechnological industries which are continually striving to obtain higher yields and improved uniformity of production. Two AI methodologies aimed at contributing to the overall intelligent monitoring and control of bioprocess operations are discussed. The development and application of a real-time knowledge-based system to provide supervisory control of fed-batch bioprocesses is reviewed. The system performs sensor validation, fault detection and diagnosis and incorporates relevant expertise and experience drawn from both bioprocess engineering and control engineering domains. A complementary approach, that of artificial neural networks is also addressed. The development of neural network modelling tools for use in bioprocess state estimation and inferential control are reviewed. An attractive characteristic of neural networks is that with the appropriate topology any non-linear functional relationship can be modelled, hence significantly reducing model-process mismatch. Results from industrial applications are presented. |
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Authors:
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M Aynsley; A Hofland; A J Morris; G A Montague; C Di Massimo |
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Publication Detail:
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Type: Journal Article; Research Support, Non-U.S. Gov't; Review |
Journal Detail:
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Title: Advances in biochemical engineering/biotechnology Volume: 48 ISSN: 0724-6145 ISO Abbreviation: Adv. Biochem. Eng. Biotechnol. Publication Date: 1993 |
Date Detail:
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Created Date: 1993-04-23 Completed Date: 1993-04-23 Revised Date: 2006-11-15 |
Medline Journal Info:
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Nlm Unique ID: 8307733 Medline TA: Adv Biochem Eng Biotechnol Country: GERMANY |
Other Details:
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Languages: eng Pagination: 1-27 Citation Subset: IM |
Affiliation:
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Department of Chemical and Process Engineering, University of Newcastle, Newcastle upon Tyne, England. |
Export Citation:
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APA/MLA Format Download EndNote Download BibTex |
| MeSH Terms | |
Descriptor/Qualifier:
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Artificial Intelligence* Biotechnology* Computer Systems Fusarium / growth & development Neural Networks (Computer) Penicillin G / metabolism Quality Control |
| Chemical | |
Reg. No./Substance:
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61-33-6/Penicillin G |
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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