Hybrid model building methodology using unsupervised fuzzy clustering and supervised neural networks

Biotechnology and Bioengineering

Volumn 77, Issue 4, 2002, Pages 420-429

  Ronen, M ^a   Shabtai, Y ^a   Guterman, H ^a  

^a BEN GURION UNIVERSITY OF THE NEGEV   (Israel)

Author keywords

Cluster validity; Fermentation; Information criteria; Neuro fuzzy model; Process modeling

Indexed keywords

COMPUTER SIMULATION; FERMENTATION; NEURAL NETWORKS; REINFORCEMENT; YEAST;

FUZZY CLUSTERING;

BIOTECHNOLOGY;

ARTICLE; AUREOBASIDIUM PULLULANS; CLUSTER ANALYSIS; FERMENTATION; FUNGUS; MATHEMATICAL ANALYSIS; METHODOLOGY; MODEL; VALIDATION PROCESS;

BIOTECHNOLOGY; CLUSTER ANALYSIS; COMPUTER SIMULATION; FERMENTATION; FUZZY LOGIC; NEURAL NETWORKS (COMPUTER);

AUREOBASIDIUM; AUREOBASIDIUM PULLULANS; FUNGI;

EID: 0037083202     PISSN: 00063592     EISSN: None     Source Type: Journal    
DOI: 10.1002/bit.10132     Document Type: Article

References (44)

1. Artificial intelligence and the supervision of bioprocesses
2. Validity-guided (re)clustering with applications to image segmentation
3. Determining model structure for neural models by network stripping
4. Pullulan synthesis by A. pullulans
5. Approximation by superpositions of a sigmoidal function
6. Towards improved penicillin fermentation via artificial neural networks
7. Experiment design considerations for non-linear system identification using neural networks
8. Unsupervised optimal fuzzy clustering
9. Artificial neural-network-based experimental-design procedures for enhancing fermentation development
10. Competitive learning from interactive activation to adaptive resonance
11. Neural networks for control systems - A survey
12. Predictive modular neural networks for time series classification
13. Expert systems in bioprocess control: Requisite features
14. Optimal brain damage
15. An introduction to computing with neural nets
16. Hierarchical neural networks
17. Local model architectures for nonlinear modeling and control
18. Local learning in local model networks
19. Identification and control of dynamical systems using neural networks
20. On cluster validity for the fuzzy c-means model
21. Nonlinear rule base model predictive control of chemical processes
22. Process identification using neural networks
23. A hybrid neural network-1st principles approach to process modeling
24. Bioprocess optimization and control - Application of hybrid modeling
25. Hybrid modeling of yeast production processes - Combination of a priori knowledge on different levels of sophistication
26. Neural networks for the production of the state of Zymomonas mobilis CP4 batch fermentations
27. A fuzzy-supported extended Kalman filter - A new approach to state estimation and prediction exemplified by alcohol formation in beer brewing
28. Fuzzy-aided neural network for real-time state estimation and process prediction in the alcohol formation step of production-scale beer brewing
29. Long-term predictions of chemical processes using recurrent neural networks - A parallel training approach
30. Structure identification of fuzzy model
31. Modeling chemical processes using prior knowledge and neural networks
32. An efficient model development strategy for bioprocesses based on neural networks in macroscopic balances. II
33. Accelerating the convergence of the backpropagation method
34. Building Sugeno-type models using fuzzy discretization and orthogonal estimation techniques
35. 30 Years of adaptive neural networks - Perception, madaline, and back-propagation
36. Artificial neural networks in process engineering
37. A validity measure for fuzzy clustering
38. Outline of a new approach to the analysis of complex systems and decision processes
39. Functional-state modeling and fuzzy control of fed-batch aerobic bakers-yeast process