PDFAbstract: In the present work, growth and cellulase production by the cellulolytic fungus Aspergillus niger in fed-batch culture using an agricultural residue as the substrate have been investigated. The Windows application of Artificial Neural Network (ANN) to the estimation of bioprocess variables is presented. A neural network methodology is discussed, which uses environmental and physiological information available from on-line sensors, to estimate the cellulase production in a fed-batch bioprocess. An efficient optimization algorithm that reduces the number of iterations required for convergence is proposed. Results are presented for different training sets and different training methodologies.
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M. Caramihai, Irina Severin. (2018) Enzyme Production Modeling Simulation Using Neural Techniques. International Journal of Biology and Biomedicine, 3 , 26-29
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