A hybrid recurrent neural network model for yeast production monitoring and control in a wine base medium

[1]  A. Holmberg.  On the practical identifiability of microbial growth models incorporating Michaelis-Menten type nonlinearities , 1982 .

[2]  L. Erickson,et al.  Estimation of yield, maintenance, and product formation kinetic parameters in anaerobic fermentations , 1984, Biotechnology and bioengineering.

[3]  Tsuneo Yamane,et al.  Fed-batch techniques in microbial processes , 1984 .

[4]  David J. Clarke,et al.  Monitoring reactor biomass , 1986 .

[5]  Georges Corrieu,et al.  Alcoholic fermentation in winemaking: On-line measurement of density and carbon dioxide evolution , 1988 .

[6]  Kumpati S. Narendra,et al.  Identification and control of dynamical systems using neural networks , 1990, IEEE Trans. Neural Networks.

[7]  J Thibault,et al.  On‐line prediction of fermentation variables using neural networks , 1990, Biotechnology and bioengineering.

[8]  Jules Thibault,et al.  Comparison of prediction performances between models obtained by the group method of data handling and neural networks for the alcoholic fermentation rate in enology , 1991 .

[9]  A. Barron.  Approximation and Estimation Bounds for Artificial Neural Networks , 1991, COLT '91.

[10]  D. Cantero,et al.  Development of a kinetic model for the alcoholic fermentation of must , 1991, Biotechnology and bioengineering.

[11]  J. Thibault.  FEEDFORWARD NEURAL NETWORKS FOR THE IDENTIFICATION OF DYNAMIC PROCESSES , 1991 .

[12]  P. Werbos,et al.  Long-term predictions of chemical processes using recurrent neural networks: a parallel training approach , 1992 .

[13]  Stephen A. Billings,et al.  Properties of neural networks with applications to modelling non-linear dynamical systems , 1992 .

[14]  M N Karim,et al.  Artificial neural networks in bioprocess state estimation. , 1992, Advances in biochemical engineering/biotechnology.

[15]  Gregory Stephanopoulos,et al.  Use of Various Measurements for Biomass Estimation , 1992 .

[16]  Pierre Roussel-Ragot,et al.  Neural Networks and Nonlinear Adaptive Filtering: Unifying Concepts and New Algorithms , 1993, Neural Computation.

[17]  Yuichi Nakamura,et al.  Approximation of dynamical systems by continuous time recurrent neural networks , 1993, Neural Networks.

[18]  Mark Collins,et al.  Empiricism Strikes Back: Neural Networks in Biotechnology , 1993, Bio/Technology.

[19]  E. Clothiaux,et al.  Neural Networks and Their Applications , 1994 .

[20]  J Morris,et al.  Neural-network contributions in biotechnology. , 1994, Trends in biotechnology.

[21]  Rimvydas Simutis,et al.  Bioprocess optimization and control: Application of hybrid modelling , 1994 .

[22]  Jules Thibault,et al.  Neural network models for final process time determination in fermented milk production , 1994 .

[23]  A Bulsari,et al.  Using feed-forward neural networks for estimation of microbial concentration in a simulated biochemical process. , 1994, Biosensors & bioelectronics.

[24]  Production de levains de tirage en champagne: influence de quelques variables opératoires , 1995 .

[25]  P. Stassi,et al.  Optimization of fermentor operations using a fermentor instrumentation system , 1995 .

[26]  Lennart Ljung,et al.  Nonlinear black-box modeling in system identification: a unified overview , 1995, Autom..

[27]  Bruno Perret,et al.  Yeast concentration estimation and prediction with static and dynamic neural network models in batch cultures , 1996 .