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Analysis of Two-Dimensional Fluorescence Spectra in Biotechnological Processes by Artificial Neural Networks II - Process Modeling using Backpropagation Neural Network -  

Lee Kum-Il (Department of Industrial Engineering, Chonnam National University, Research Center for Biophotonics)
Yim Yong-Sik (Department of Industrial Engineering, Chonnam National University, BioProcess Technology Lab.)
Sohn Ok-Jae (Department of Industrial Engineering, Chonnam National University, BioProcess Technology Lab.)
Chung Sang-Wook (Department of Industrial Engineering, Chonnam National University, Research Center for Biophotonics)
Rhee Jong Il (Faculty of Applied Chemical Engineering, Chonnam National University, BioProcess Technology Lab.)
Publication Information
KSBB Journal / v.20, no.4, 2005 , pp. 299-304 More about this Journal
Abstract
A two-dimensional (2D) spectrofluorometer was used to monitor various fermentation processes with recombinant E. coli for the production of 5-aminolevulinic acid (ALA). The whole fluorescence spectral data obtained during a process were analyed using artificial neural networks, i.e. self-organizing map (SOM) and feedforward backpropagation neural network (BPNN).Based on the classified fluorescence spectra a supervised BPNN algorithm was used to predict some of the process parameters. It was also shown that the BPNN models could elucidate some sections of the process performance, e.g. forecasting the process performance.
Keywords
5-aminolevulinic acid; artificial neural networks; fermentation; 2D fluorescence spectra; recombinant E. coli;
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