Prediction of the isotherms of human IgG adsorption on Ni(II)-IDA-PEVA membrane using artificial neural networks
| Autor: | Jones Erni Schmitz, Igor Tadeu Lazzarotto Bresolin |
|---|---|
| Rok vydání: | 2014 |
| Předmět: |
Artificial neural network
Chemistry General Chemical Engineering Computer Science::Neural and Evolutionary Computation Analytical chemistry Langmuir adsorption model Surfaces and Interfaces General Chemistry Human Immunoglobulin G Bayesian interpretation of regularization symbols.namesake Membrane Adsorption symbols Fiber Biological system Interpolation |
| Zdroj: | Adsorption. 20:959-965 |
| ISSN: | 1572-8757 0929-5607 |
| DOI: | 10.1007/s10450-014-9641-9 |
| Popis: | The use of artificial neural networks (ANNs) to predict the adsorption isotherms of human immunoglobulin G on immobilized Ni(II) affinity hollow fiber membranes was studied. Neural networks were trained using the Levenberg–Marquardt algorithm combined with Bayesian regularization technique and experimental data from different temperatures. The resulting neural network demonstrated to be able to interpolate the behavior of the maximum adsorption capacity and equilibrium concentration in the temperature range (4, 37 °C) with correlation coefficients higher than 0.96. Results demonstrated to be very similar to those achieved with traditionally Langmuir model adjustment. The advantage of interpolation ability of ANNs was also showed. |
| Databáze: | OpenAIRE |
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