Abstract
DDGS is the major coproduct generated from the fermentation of grain, but it is high in protein and an inexpensive source of protein. To optimize the extracting process of protein from DDGS, two different artificial intelligence techniques namely artificial neural network(ANN) and genetic algorithm(GA) have been developed using the three influential process variables as model inputs and the extraction rate of protein as the model output. The correlation coefficient for the ANN model were 0.98664. The input parameters of ANN model were subsequently optimized using the GA. The ANN-GA model predicted a maximum extraction rate of 0.424 g/2 g DDGS which gave a 15.46% increase of extraction rate over the statistical optimization. It was in good agreement with the actual experiment under the optimum conditions.
This work is supported by foundation for Young Scholars of Harbin Normal University #KGB200806.
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Dong, Y. et al. (2012). Artificial Intelligence Based Optimization of the Extracting Process of Protein from DDGS Using Alkali Method. In: Zhu, E., Sambath, S. (eds) Information Technology and Agricultural Engineering. Advances in Intelligent and Soft Computing, vol 134. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27537-1_18
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DOI: https://doi.org/10.1007/978-3-642-27537-1_18
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