Simulation of Supercritical CO2 Extraction for Peanut Oil Based on Artificial Neural Networks

Abstract:

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The BP ANN was established based on MATLAB to simulate the supercritical CO2 extraction process for extracting peanut oil. The supercritical CO2 extraction experiment for peanut oil was carried out and the experimental results were used to train the BP ANN. The operating pressure, temperature and time were regarded as the inputs of the BP ANN and the percentage extraction as the output. By testing the BP ANN with other groups of experimental data, the precision of the BP ANN was verified. This BP ANN can predict the percentage extraction when the processing parameters of supercritical CO2 extraction are given, and the optimization of the processing parameters can also be realized.

Info:

Periodical:

Edited by:

Yi-Min Deng, Aibing Yu, Weihua Li and Di Zheng

Pages:

1172-1175

DOI:

10.4028/www.scientific.net/AMM.37-38.1172

Citation:

J. S. Dong and B. Q. Gu, "Simulation of Supercritical CO2 Extraction for Peanut Oil Based on Artificial Neural Networks", Applied Mechanics and Materials, Vols. 37-38, pp. 1172-1175, 2010

Online since:

November 2010

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$35.00

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