Modeling of an industrial process of pleuromutilin fermentation using feed-forward neural networks

Brazilian Journal of Chemical Engineering

L. Khaouane¹  O. Benkortbi¹  S. Hanini¹  C. Si-moussa¹ 

[1] ,Université de Médéa26000 Médéa ,Algeria

关键词: Modeling;    Pleuromutilin;    Fermentation;    Feed-forward neural networks;   

DOI  :  10.1590/S0104-66322013000100012

来源: SciELO

【 摘 要 】

This work investigates the use of artificial neural networks in modeling an industrial fermentation process of Pleuromutilin produced by Pleurotus mutilus in a fed-batch mode. Three feed-forward neural network models characterized by a similar structure (five neurons in the input layer, one hidden layer and one neuron in the output layer) are constructed and optimized with the aim to predict the evolution of three main bioprocess variables: biomass, substrate and product. Results show a good fit between the predicted and experimental values for each model (the root mean squared errors were 0.4624% - 0.1234 g/L and 0.0016 mg/g respectively). Furthermore, the comparison between the optimized models and the unstructured kinetic models in terms of simulation results shows that neural network models gave more significant results. These results encourage further studies to integrate the mathematical formulae extracted from these models into an industrial control loop of the process.

【 授权许可】

CC BY   
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