Predicting the Removal Amount of SCN- by TiO2 NPs Using ANN Methods
Using Novel Artificial Neural Network Methods in Removing Aqueous Thiocyanate Anions by Titanium Dioxide Nanoparticles
(Sprache: Englisch)
In this work, the adsorbent method is performed using artificial neural network (ANN) modeling. The adsorbent is applied for removal of Thiocyanate in water samples using Titanium Dioxide (TiO2) nanoparticles as effective sorbent. Prediction amount of...
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In this work, the adsorbent method is performed using artificial neural network (ANN) modeling. The adsorbent is applied for removal of Thiocyanate in water samples using Titanium Dioxide (TiO2) nanoparticles as effective sorbent. Prediction amount of Thiocyanate removal was investigated with novel algorithms of neural network. For this purpose, six parameters were chosen as training input data of neural network functions including pH, time of stirring, the mass of adsorbent, volume of TiO2, volume of Fe (III), and volume of buffer. Performances of the suggested methods were examined using statistical parameters and found that it is an efficient, effective modeling satisfactory outputs. The radial basis function (RBF) and Levenberg-Marquardt (LM) algorithm could accurately predict the experimental data with correlation coefficient of 0.997939 and 0.99931, respectively. The Pearson's Chi-square measure was found to be 29.00 for most variables, indicating that these variables are likely to be dependent in some way.
Autoren-Porträt von Rashin Andayesh
Andayesh, RashinRashin Andayesh has always dreamed of becoming a chemist, but it didn't give her a sense of serenity and peace of mind when she had environmental concerns. Rashin achieved her goal and hold an MSc degree in Analytical Chemistry and now, she is a PhD student in University of South Australia to fulfill her ambition about Environmental Science.
Bibliographische Angaben
- Autor: Rashin Andayesh
- 2020, 52 Seiten, Maße: 22 cm, Kartoniert (TB), Englisch
- Verlag: LAP Lambert Academic Publishing
- ISBN-10: 6202514078
- ISBN-13: 9786202514071
Sprache:
Englisch
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