Paper Title:
Simulation of Supercritical CO2 Extraction for Peanut Oil Based on Artificial Neural Networks
  Abstract

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, 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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Price
$32.00
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