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化学工业与工程
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��ѧ��ҵ�빤�� 2004, Vol. 21 Issue (3) :189-192    DOI:
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Prediction of Solid Solubility in Supercritical Fluid by Using BP Neural Newtork
LIAO Hai-qing~1,WU Da-ke~1,CHEN Shu-lin~2 (1.College of Chemical and Bio-engineering,Guizhou University of Technology,Guizhou Guiyang 550003,China; 2.Center of Chemical Analysis,Guizhou University of Technology,Guizhou Guiyang 550003,China)
(1.College of Chemical and Bio-engineering,Guizhou University of Technology,Guizhou Guiyang 550003,China; 2.Center of Chemical Analysis,Guizhou University of Technology,Guizhou Guiyang 550003,China
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Abstract�� An error back propagation (EBP) artificial neural network with Vogl algorithm was constructed to predict the solubilities of different solids in supercritical fluids.612 experimental point for 21 systems had been trained and predicted,the predicting total average relative error is 4.02%.This method is superior to equation of state method.
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Received 2004-05-15; published 2004-05-15
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�κ���,����,������.Ӧ��BP������Ԥ������ڳ��ٽ������е��ܽ��[J].  ��ѧ��ҵ�빤��, 2004,21(3): 189-192
LIAO Hai-qing~1,WU Da-ke~1,CHEN Shu-lin~2 .Prediction of Solid Solubility in Supercritical Fluid by Using BP Neural Newtork[J].  Chemcial Industry and Engineering, 2004,21(3): 189-192
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