Please use this identifier to cite or link to this item:
|Type:||Artigo de periódico|
|Title:||Neural modeling for cytochrome b5 extraction|
|Abstract:||In this work a neural model for cytochrome b5 extraction in batch and in continuous operation was developed. The best feedforward arquiteture achieved for batch operation modeling was 3-4-1 and 3-8-2 for the continuous operation. It was observed that among the models developed, the best adjustment was that obtained with Bayesian regularization algorithm training. Deviations of less than 10% were observed for the experimental data and they are similar for the neural model, since it was statistically proved the null hypothesis in the comparison between the two independent samples (experimental and predicted outputs). (c) 2006 Elsevier Ltd. All rights reserved.|
|Editor:||Elsevier Sci Ltd|
|Citation:||Process Biochemistry. Elsevier Sci Ltd, v. 41, n. 6, n. 1272, n. 1275, 2006.|
|Appears in Collections:||Unicamp - Artigos e Outros Documentos|
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.