An efficient model development strategy for bioprocesses based on neural networks in macroscopic balances: Part II

Biotechnology and Bioengineering

Volumn 62, Issue 6, 1999, Pages 666-680

  Van Can, H J L ^a,b   Te Braake, H A B ^a   Bijman, A ^a   Hellinga, C ^a   Luyben, K Ch A M ^a   Heijnen, J J ^a  

^a DELFT UNIVERSITY OF TECHNOLOGY   (Netherlands)

^b Dept of Engineering and Automation ^*  (Netherlands)

Author keywords

Extrapolation; Hybrid models; Neural networks; Penicillin G

Indexed keywords

ANTIBIOTICS; ENZYMES; EXTRAPOLATION; MATHEMATICAL MODELS; NEURAL NETWORKS;

SERIAL GRAY BOX MODEL;

BIOCONVERSION;

6 AMINOPENICILLANIC ACID; PENICILLIN G;

ACCURACY; ARTICLE; ARTIFICIAL NEURAL NETWORK; BIOPROCESS; CONTROLLED STUDY; FREQUENCY ANALYSIS; INTERMETHOD COMPARISON; PREDICTION; REACTION ANALYSIS; RELIABILITY; SIMULATION; VALIDATION PROCESS;

EID: 0033586406     PISSN: 00063592     EISSN: None     Source Type: Journal    
DOI: 10.1002/(SICI)1097-0290(19990320)62:6<666::AID-BIT6>3.0.CO;2-S     Document Type: Article

References (17)

1. Albiol J, Campmajo C. Casas C. Poch M. 1995. Biomass estimation in plant cell cultures: A neural network approach. Biotechnol Prog 11: 88-92.
2. Dors M, Simutis R, Lübbert A. 1995. Advanced supervision of mammalian cell cultures using hybrid process models. In: Munack A, Schügerl K, editors. Preprints of the 6th international conference on computer applications in biotechnology, p 72-77.
3. Duan G, Chen JY. 1996. Kinetic analysis of the effect of product removal on the hydrolysis of penicillin G by immobilised penicillin acylase. Process Biochem 31:27-30.
4. Kell DB, Sonnleitner B. 1995. GMP-Good modeling practice: An essential component of good manufacturing practice. Trends Biotechnol 13: 481-492.
5. Lee SB, Dewey D, Ryu DY. 1982. Reaction kinetics and mechanisms of penicillin amidase: A comparative study by computer simulation. Enzyme Microb Technol 4:35-38.
6. Montague G, Morris J. 1994. Neural-network contributions in biotechnology. Trends Biotechnol 12:312-324.
7. Psichogios DC, Ungar LH. 1992. A hybrid neural network-first principles approach to process modeling. AIChE J 38:1499-1511.
8. Schubert J, Simutis R, Dors M, Havlik I, Lübbert A. 1994. Bioprocess optimization and control: Application of hybrid modeling. J Biotechnol 35:51-68.
9. Simutis R, Havlik I, Dors M, Lübbert A. 1995. Artificial neural networks of improved reliability for industrial process supervision. In: Munack A, Schügerl K, editors. Preprints of the 6th international conference on computer applications in biotechnology, p 59-65.
10. Te Braake HAB, van Can HJL, Van Straten G, Verbruggen HB. 1996. Regulated activation weights neural network (RAWN). ESANN '96. Brugge Belgium: p 19-24.
11. Thompson ML, Kramer MA. 1994. Modeling chemical processes using prior knowledge and neural networks, AIChE J 40:1328-1340.
12. Tholudur A, Ramirez F. 1996. Optimization of fed-batch bioreactors using neural network parameter function models. Biotechnol Prog 12: 302-309.
13. van Can HJL, Te Braake HAB, Hellinga C, Luyben KChAM, Heijnen JJ. 1996. A strategy for dynamic process modeling based on neural networks in macroscopic balances. AIChE J 42:3403-3418.
14. van Can HJL, Te Braake HAB, Hellinga C, Luyben KChAM, Heijnen JJ. 1997. An efficient model development strategy for bioprocesses based on neural networks in macroscopic balances. Part I. Biotechnol Bioeng 54:549-566.
15. Warburton D, Dunnill P, Lilly MD. 1973. Conversion of benzylpenicillin to 6-aminopenicillanic acid in a batch reactor and continuous feed stirred tank reactor using immobilized penicillin amidase. Biotechnol Bioeng 15:13-25.
16. Warnes MR, Glassey J, Montague GA, Kara B. 1996. On data-based modeling techniques for fermentation processes. Process Biochem 31: 147-155.
17. Zhang Q, Reid FR, Lichtfield JB, Ren J, Chang S-W. 1994. A prototype neural network supervised control system for Bacillus thuringiensis fermentations. Biotechnol Bioeng 43:483-489.